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Since then, the mean-variance model has played a crucial role in single-period portfolio optimization theory and practice. In this... <a class="more_link u-tcGrayDark u-linkUnstyled" data-container=".work_76283366" data-show=".complete" data-hide=".summarized" data-more-link-behavior="true" href="#">more</a></div><div class="complete hidden">In 1950 Markowitz first formalized the portfolio optimization problem in terms of mean return and variance. Since then, the mean-variance model has played a crucial role in single-period portfolio optimization theory and practice. In this paper we study the optimal portfolio selection problem in a multi-period framework, by considering fixed and proportional transaction costs and evaluating how much they affect a re-investment strategy. Specifically, we modify the single-period portfolio optimization model, based on the Conditional Value at Risk (CVaR) as measure of risk, to introduce portfolio rebalancing. The aim is to provide investors and financial institutions with an effective tool to better exploit new information made available by the market. We then suggest a procedure to use the proposed optimization model in a multi-period framework. Extensive computational results based on different historical data sets from German Stock Exchange Market (XETRA) are presented.</div></div></div><ul class="InlineList u-ph0x u-fs13"><li class="InlineList-item logged_in_only"><div class="share_on_academia_work_button"><a class="academia_share Button Button--inverseBlue Button--sm js-bookmark-button" data-academia-share="Work/76283366" data-share-source="work_strip" data-spinner="small_white_hide_contents"><i class="fa fa-plus"></i><span class="work-strip-link-text u-ml1x" data-content="button_text">Bookmark</span></a></div></li><li class="InlineList-item"><div class="download"><a id="46114cb2dca7da1c9dd7553742b8781c" rel="nofollow" data-download="{"attachment_id":84038085,"asset_id":76283366,"asset_type":"Work","always_allow_download":false,"track":null,"button_location":"work_strip","source":null,"hide_modal":null}" class="Button Button--sm Button--inverseGreen js-download-button prompt_button doc_download" href="https://www.academia.edu/attachments/84038085/download_file?st=MTc0MDU1NDU5OCw4LjIyMi4yMDguMTQ2&s=work_strip"><i class="fa fa-arrow-circle-o-down fa-lg"></i><span class="u-textUppercase u-ml1x" data-content="button_text">Download</span></a></div></li><li class="InlineList-item"><ul class="InlineList InlineList--bordered u-ph0x"><li class="InlineList-item InlineList-item--bordered"><span class="InlineList-item-text">by <span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a class="u-tcGrayDark u-fw700" data-has-card-for-user="47627494" href="https://brescia-it.academia.edu/RMansini">R. 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Since then, the mean-variance model has played a crucial role in single-period portfolio optimization theory and practice. In this paper we study the optimal portfolio selection problem in a multi-period framework, by considering fixed and proportional transaction costs and evaluating how much they affect a re-investment strategy. Specifically, we modify the single-period portfolio optimization model, based on the Conditional Value at Risk (CVaR) as measure of risk, to introduce portfolio rebalancing. The aim is to provide investors and financial institutions with an effective tool to better exploit new information made available by the market. We then suggest a procedure to use the proposed optimization model in a multi-period framework. Extensive computational results based on different historical data sets from German Stock Exchange Market (XETRA) are presented.","downloadable_attachments":[{"id":84038085,"asset_id":76283366,"asset_type":"Work","always_allow_download":false}],"ordered_authors":[{"id":47627494,"first_name":"R.","last_name":"Mansini","domain_name":"brescia-it","page_name":"RMansini","display_name":"R. Mansini","profile_url":"https://brescia-it.academia.edu/RMansini?f_ri=725","photo":"/images/s65_no_pic.png"}],"research_interests":[{"id":725,"name":"Computational Economics","url":"https://www.academia.edu/Documents/in/Computational_Economics?f_ri=725","nofollow":true},{"id":747,"name":"Econometrics","url":"https://www.academia.edu/Documents/in/Econometrics?f_ri=725","nofollow":true},{"id":11820,"name":"Modeling and Simulation","url":"https://www.academia.edu/Documents/in/Modeling_and_Simulation?f_ri=725","nofollow":true},{"id":12061,"name":"Risk Management","url":"https://www.academia.edu/Documents/in/Risk_Management?f_ri=725","nofollow":true},{"id":56735,"name":"Portfolio Optimization","url":"https://www.academia.edu/Documents/in/Portfolio_Optimization?f_ri=725"},{"id":105569,"name":"Financial Institutions","url":"https://www.academia.edu/Documents/in/Financial_Institutions?f_ri=725"},{"id":208947,"name":"Theory and Practice","url":"https://www.academia.edu/Documents/in/Theory_and_Practice?f_ri=725"},{"id":221822,"name":"Historical Data","url":"https://www.academia.edu/Documents/in/Historical_Data?f_ri=725"},{"id":311931,"name":"STOCK EXCHANGE","url":"https://www.academia.edu/Documents/in/STOCK_EXCHANGE?f_ri=725"},{"id":639625,"name":"Investment Strategies","url":"https://www.academia.edu/Documents/in/Investment_Strategies?f_ri=725"},{"id":1817786,"name":"Conditional Value at Risk","url":"https://www.academia.edu/Documents/in/Conditional_Value_at_Risk?f_ri=725"},{"id":2157649,"name":"Mean-variance analysis","url":"https://www.academia.edu/Documents/in/Mean-variance_analysis?f_ri=725"},{"id":2631911,"name":"Portfolio analysis","url":"https://www.academia.edu/Documents/in/Portfolio_analysis?f_ri=725"},{"id":3079413,"name":"Finance and Investment Banking Area","url":"https://www.academia.edu/Documents/in/Finance_and_Investment_Banking_Area?f_ri=725"},{"id":3079415,"name":"Finance and Investment Banking","url":"https://www.academia.edu/Documents/in/Finance_and_Investment_Banking?f_ri=725"}]}, }) } })();</script></ul></li></ul></div></div><div class="u-borderBottom1 u-borderColorGrayLighter"><div class="clearfix u-pv7x u-mb0x js-work-card work_14121238" data-work_id="14121238" itemscope="itemscope" itemtype="https://schema.org/ScholarlyArticle"><div class="header"><div class="title u-fontSerif u-fs22 u-lineHeight1_3"><a class="u-tcGrayDarkest js-work-link" href="https://www.academia.edu/14121238/Bicriteria_Decision_Making_and_Financial_Equilibrium_A_Variational_Inequality_Perspective">Bicriteria Decision Making and Financial Equilibrium: A Variational Inequality Perspective</a></div></div><div class="u-pb4x u-mt3x"><div class="summary u-fs14 u-fw300 u-lineHeight1_5 u-tcGrayDarkest"><div class="summarized">In this paper we develop a framework for the study of financial equilibrium in the case of sectors in the economy, each of which is faced with two objectives/criteria in his portfolio selection decision making. In particular, we first... <a class="more_link u-tcGrayDark u-linkUnstyled" data-container=".work_14121238" data-show=".complete" data-hide=".summarized" data-more-link-behavior="true" href="#">more</a></div><div class="complete hidden">In this paper we develop a framework for the study of financial equilibrium in the case of sectors in the economy, each of which is faced with two objectives/criteria in his portfolio selection decision making. In particular, we first present the bicriteria decision model of an individual financial sector, who seeks an optimal portfolio composition, given that the wishes to</div></div></div><ul class="InlineList u-ph0x u-fs13"><li class="InlineList-item logged_in_only"><div class="share_on_academia_work_button"><a class="academia_share Button Button--inverseBlue Button--sm js-bookmark-button" data-academia-share="Work/14121238" data-share-source="work_strip" data-spinner="small_white_hide_contents"><i class="fa fa-plus"></i><span class="work-strip-link-text u-ml1x" data-content="button_text">Bookmark</span></a></div></li><li class="InlineList-item"><div class="download"><a id="63b366b7f1b1398ce5f00a2a2af3cf78" rel="nofollow" data-download="{"attachment_id":44583641,"asset_id":14121238,"asset_type":"Work","always_allow_download":false,"track":null,"button_location":"work_strip","source":null,"hide_modal":null}" class="Button Button--sm Button--inverseGreen js-download-button prompt_button doc_download" href="https://www.academia.edu/attachments/44583641/download_file?st=MTc0MDU1NDU5OCw4LjIyMi4yMDguMTQ2&s=work_strip"><i class="fa fa-arrow-circle-o-down fa-lg"></i><span class="u-textUppercase u-ml1x" data-content="button_text">Download</span></a></div></li><li class="InlineList-item"><ul class="InlineList InlineList--bordered u-ph0x"><li class="InlineList-item InlineList-item--bordered"><span class="InlineList-item-text">by <span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a class="u-tcGrayDark u-fw700" data-has-card-for-user="33119007" href="https://independent.academia.edu/AnnaNagurney">Anna Nagurney</a><script data-card-contents-for-user="33119007" type="text/json">{"id":33119007,"first_name":"Anna","last_name":"Nagurney","domain_name":"independent","page_name":"AnnaNagurney","display_name":"Anna Nagurney","profile_url":"https://independent.academia.edu/AnnaNagurney?f_ri=725","photo":"/images/s65_no_pic.png"}</script></span></span></li><li class="js-paper-rank-work_14121238 InlineList-item InlineList-item--bordered hidden"><span class="js-paper-rank-view hidden u-tcGrayDark" data-paper-rank-work-id="14121238"><i class="u-m1x fa fa-bar-chart"></i><strong class="js-paper-rank"></strong></span><script>$(function() { new Works.PaperRankView({ workId: 14121238, container: ".js-paper-rank-work_14121238", }); 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$(".js-view-count[data-work-id=14121238]").text(description); $(".js-view-count-work_14121238").attr('title', description).tooltip(); }); });</script></span><script>$(function() { $(".js-view-count-work_14121238").removeClass('hidden') })</script></div></li><li class="InlineList-item u-positionRelative" style="max-width: 250px"><div class="u-positionAbsolute" data-has-card-for-ri-list="14121238"><i class="fa fa-tag InlineList-item-icon u-positionRelative"></i>  <a class="InlineList-item-text u-positionRelative">12</a>  </div><span class="InlineList-item-text u-textTruncate u-pl10x"><a class="InlineList-item-text" data-has-card-for-ri="725" rel="nofollow" href="https://www.academia.edu/Documents/in/Computational_Economics">Computational Economics</a>, <script data-card-contents-for-ri="725" type="text/json">{"id":725,"name":"Computational Economics","url":"https://www.academia.edu/Documents/in/Computational_Economics?f_ri=725","nofollow":true}</script><a class="InlineList-item-text" data-has-card-for-ri="747" rel="nofollow" href="https://www.academia.edu/Documents/in/Econometrics">Econometrics</a>, <script data-card-contents-for-ri="747" type="text/json">{"id":747,"name":"Econometrics","url":"https://www.academia.edu/Documents/in/Econometrics?f_ri=725","nofollow":true}</script><a class="InlineList-item-text" data-has-card-for-ri="1681" rel="nofollow" href="https://www.academia.edu/Documents/in/Decision_Making">Decision Making</a>, <script data-card-contents-for-ri="1681" type="text/json">{"id":1681,"name":"Decision Making","url":"https://www.academia.edu/Documents/in/Decision_Making?f_ri=725","nofollow":true}</script><a class="InlineList-item-text" data-has-card-for-ri="46254" rel="nofollow" href="https://www.academia.edu/Documents/in/Optimization_Problem">Optimization Problem</a><script data-card-contents-for-ri="46254" type="text/json">{"id":46254,"name":"Optimization Problem","url":"https://www.academia.edu/Documents/in/Optimization_Problem?f_ri=725","nofollow":true}</script></span></li><script>(function(){ if (true) { new Aedu.ResearchInterestListCard({ el: $('*[data-has-card-for-ri-list=14121238]'), work: {"id":14121238,"title":"Bicriteria Decision Making and Financial Equilibrium: A Variational Inequality Perspective","created_at":"2015-07-16T09:32:45.220-07:00","url":"https://www.academia.edu/14121238/Bicriteria_Decision_Making_and_Financial_Equilibrium_A_Variational_Inequality_Perspective?f_ri=725","dom_id":"work_14121238","summary":"In this paper we develop a framework for the study of financial equilibrium in the case of sectors in the economy, each of which is faced with two objectives/criteria in his portfolio selection decision making. In particular, we first present the bicriteria decision model of an individual financial sector, who seeks an optimal portfolio composition, given that the wishes to","downloadable_attachments":[{"id":44583641,"asset_id":14121238,"asset_type":"Work","always_allow_download":false}],"ordered_authors":[{"id":33119007,"first_name":"Anna","last_name":"Nagurney","domain_name":"independent","page_name":"AnnaNagurney","display_name":"Anna Nagurney","profile_url":"https://independent.academia.edu/AnnaNagurney?f_ri=725","photo":"/images/s65_no_pic.png"}],"research_interests":[{"id":725,"name":"Computational Economics","url":"https://www.academia.edu/Documents/in/Computational_Economics?f_ri=725","nofollow":true},{"id":747,"name":"Econometrics","url":"https://www.academia.edu/Documents/in/Econometrics?f_ri=725","nofollow":true},{"id":1681,"name":"Decision Making","url":"https://www.academia.edu/Documents/in/Decision_Making?f_ri=725","nofollow":true},{"id":46254,"name":"Optimization Problem","url":"https://www.academia.edu/Documents/in/Optimization_Problem?f_ri=725","nofollow":true},{"id":56735,"name":"Portfolio Optimization","url":"https://www.academia.edu/Documents/in/Portfolio_Optimization?f_ri=725"},{"id":80072,"name":"Economic System","url":"https://www.academia.edu/Documents/in/Economic_System?f_ri=725"},{"id":98846,"name":"Multicriteria decision making","url":"https://www.academia.edu/Documents/in/Multicriteria_decision_making?f_ri=725"},{"id":102003,"name":"Variational Inequality Problems","url":"https://www.academia.edu/Documents/in/Variational_Inequality_Problems?f_ri=725"},{"id":244811,"name":"Financial Sector","url":"https://www.academia.edu/Documents/in/Financial_Sector?f_ri=725"},{"id":871906,"name":"Decision Models","url":"https://www.academia.edu/Documents/in/Decision_Models?f_ri=725"},{"id":886557,"name":"Portfolio Selection","url":"https://www.academia.edu/Documents/in/Portfolio_Selection?f_ri=725"},{"id":1980640,"name":"State dependence","url":"https://www.academia.edu/Documents/in/State_dependence?f_ri=725"}]}, }) } })();</script></ul></li></ul></div></div><div class="u-borderBottom1 u-borderColorGrayLighter"><div class="clearfix u-pv7x u-mb0x js-work-card work_77361176" data-work_id="77361176" itemscope="itemscope" itemtype="https://schema.org/ScholarlyArticle"><div class="header"><div class="title u-fontSerif u-fs22 u-lineHeight1_3"><a class="u-tcGrayDarkest js-work-link" href="https://www.academia.edu/77361176/Explainable_AI_in_Credit_Risk_Management">Explainable AI in Credit Risk Management</a></div></div><div class="u-pb4x u-mt3x"><div class="summary u-fs14 u-fw300 u-lineHeight1_5 u-tcGrayDarkest"><div class="summarized">The paper proposes an explainable Artificial Intelligence model that can be used in credit risk management and, in particular, in measuring the risks that arise when credit is borrowed employing peer to peer lending platforms. The model... <a class="more_link u-tcGrayDark u-linkUnstyled" data-container=".work_77361176" data-show=".complete" data-hide=".summarized" data-more-link-behavior="true" href="#">more</a></div><div class="complete hidden">The paper proposes an explainable Artificial Intelligence model that can be used in credit risk management and, in particular, in measuring the risks that arise when credit is borrowed employing peer to peer lending platforms. The model applies correlation networks to Shapley values so that Artificial Intelligence predictions are grouped according to the similarity in the underlying explanations. The empirical analysis of 15,000 small and medium companies asking for credit reveals that both risky and not risky borrowers can be grouped according to a set of similar financial characteristics, which can be employed to explain their credit score and, therefore, to predict their future behaviour.</div></div></div><ul class="InlineList u-ph0x u-fs13"><li class="InlineList-item logged_in_only"><div class="share_on_academia_work_button"><a class="academia_share Button Button--inverseBlue Button--sm js-bookmark-button" data-academia-share="Work/77361176" data-share-source="work_strip" data-spinner="small_white_hide_contents"><i class="fa fa-plus"></i><span class="work-strip-link-text u-ml1x" data-content="button_text">Bookmark</span></a></div></li><li class="InlineList-item"><div class="download"><a id="f7a2d612201c40b24161ef09acdcd4d9" rel="nofollow" data-download="{"attachment_id":84754040,"asset_id":77361176,"asset_type":"Work","always_allow_download":false,"track":null,"button_location":"work_strip","source":null,"hide_modal":null}" class="Button Button--sm Button--inverseGreen js-download-button prompt_button doc_download" href="https://www.academia.edu/attachments/84754040/download_file?st=MTc0MDU1NDU5OCw4LjIyMi4yMDguMTQ2&s=work_strip"><i class="fa fa-arrow-circle-o-down fa-lg"></i><span class="u-textUppercase u-ml1x" data-content="button_text">Download</span></a></div></li><li class="InlineList-item"><ul class="InlineList InlineList--bordered u-ph0x"><li class="InlineList-item InlineList-item--bordered"><span class="InlineList-item-text">by <span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a class="u-tcGrayDark u-fw700" data-has-card-for-user="3198024" href="https://unipv.academia.edu/paologiudici">Paolo Giudici</a><script data-card-contents-for-user="3198024" type="text/json">{"id":3198024,"first_name":"Paolo","last_name":"Giudici","domain_name":"unipv","page_name":"paologiudici","display_name":"Paolo Giudici","profile_url":"https://unipv.academia.edu/paologiudici?f_ri=725","photo":"https://0.academia-photos.com/3198024/1051863/19833143/s65_paolo.giudici.jpg"}</script></span></span></li><li class="js-paper-rank-work_77361176 InlineList-item InlineList-item--bordered hidden"><span class="js-paper-rank-view hidden u-tcGrayDark" data-paper-rank-work-id="77361176"><i class="u-m1x fa fa-bar-chart"></i><strong class="js-paper-rank"></strong></span><script>$(function() { new Works.PaperRankView({ workId: 77361176, container: ".js-paper-rank-work_77361176", }); 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$(".js-view-count[data-work-id=77361176]").text(description); $(".js-view-count-work_77361176").attr('title', description).tooltip(); }); });</script></span><script>$(function() { $(".js-view-count-work_77361176").removeClass('hidden') })</script></div></li><li class="InlineList-item u-positionRelative" style="max-width: 250px"><div class="u-positionAbsolute" data-has-card-for-ri-list="77361176"><i class="fa fa-tag InlineList-item-icon u-positionRelative"></i>  <a class="InlineList-item-text u-positionRelative">7</a>  </div><span class="InlineList-item-text u-textTruncate u-pl9x"><a class="InlineList-item-text" data-has-card-for-ri="26" rel="nofollow" href="https://www.academia.edu/Documents/in/Business">Business</a>, <script data-card-contents-for-ri="26" type="text/json">{"id":26,"name":"Business","url":"https://www.academia.edu/Documents/in/Business?f_ri=725","nofollow":true}</script><a class="InlineList-item-text" data-has-card-for-ri="725" rel="nofollow" href="https://www.academia.edu/Documents/in/Computational_Economics">Computational Economics</a>, <script data-card-contents-for-ri="725" type="text/json">{"id":725,"name":"Computational Economics","url":"https://www.academia.edu/Documents/in/Computational_Economics?f_ri=725","nofollow":true}</script><a class="InlineList-item-text" data-has-card-for-ri="747" rel="nofollow" href="https://www.academia.edu/Documents/in/Econometrics">Econometrics</a>, <script data-card-contents-for-ri="747" type="text/json">{"id":747,"name":"Econometrics","url":"https://www.academia.edu/Documents/in/Econometrics?f_ri=725","nofollow":true}</script><a class="InlineList-item-text" data-has-card-for-ri="69856" rel="nofollow" href="https://www.academia.edu/Documents/in/Social_Science_Research_Network">Social Science Research Network</a><script data-card-contents-for-ri="69856" type="text/json">{"id":69856,"name":"Social Science Research Network","url":"https://www.academia.edu/Documents/in/Social_Science_Research_Network?f_ri=725","nofollow":true}</script></span></li><script>(function(){ if (true) { new Aedu.ResearchInterestListCard({ el: $('*[data-has-card-for-ri-list=77361176]'), work: {"id":77361176,"title":"Explainable AI in Credit Risk Management","created_at":"2022-04-23T07:05:46.739-07:00","url":"https://www.academia.edu/77361176/Explainable_AI_in_Credit_Risk_Management?f_ri=725","dom_id":"work_77361176","summary":"The paper proposes an explainable Artificial Intelligence model that can be used in credit risk management and, in particular, in measuring the risks that arise when credit is borrowed employing peer to peer lending platforms. The model applies correlation networks to Shapley values so that Artificial Intelligence predictions are grouped according to the similarity in the underlying explanations. The empirical analysis of 15,000 small and medium companies asking for credit reveals that both risky and not risky borrowers can be grouped according to a set of similar financial characteristics, which can be employed to explain their credit score and, therefore, to predict their future behaviour.","downloadable_attachments":[{"id":84754040,"asset_id":77361176,"asset_type":"Work","always_allow_download":false}],"ordered_authors":[{"id":3198024,"first_name":"Paolo","last_name":"Giudici","domain_name":"unipv","page_name":"paologiudici","display_name":"Paolo Giudici","profile_url":"https://unipv.academia.edu/paologiudici?f_ri=725","photo":"https://0.academia-photos.com/3198024/1051863/19833143/s65_paolo.giudici.jpg"}],"research_interests":[{"id":26,"name":"Business","url":"https://www.academia.edu/Documents/in/Business?f_ri=725","nofollow":true},{"id":725,"name":"Computational Economics","url":"https://www.academia.edu/Documents/in/Computational_Economics?f_ri=725","nofollow":true},{"id":747,"name":"Econometrics","url":"https://www.academia.edu/Documents/in/Econometrics?f_ri=725","nofollow":true},{"id":69856,"name":"Social Science Research Network","url":"https://www.academia.edu/Documents/in/Social_Science_Research_Network?f_ri=725","nofollow":true},{"id":85998,"name":"Credit Risk","url":"https://www.academia.edu/Documents/in/Credit_Risk?f_ri=725"},{"id":1554562,"name":"Cornell University","url":"https://www.academia.edu/Documents/in/Cornell_University?f_ri=725"},{"id":3079415,"name":"Finance and Investment Banking","url":"https://www.academia.edu/Documents/in/Finance_and_Investment_Banking?f_ri=725"}]}, }) } })();</script></ul></li></ul></div></div><div class="u-borderBottom1 u-borderColorGrayLighter"><div class="clearfix u-pv7x u-mb0x js-work-card work_68296346" data-work_id="68296346" itemscope="itemscope" itemtype="https://schema.org/ScholarlyArticle"><div class="header"><div class="title u-fontSerif u-fs22 u-lineHeight1_3"><a class="u-tcGrayDarkest js-work-link" href="https://www.academia.edu/68296346/A_dynamic_aggregate_supply_and_aggregate_demand_model_with_Matlab">A dynamic aggregate supply and aggregate demand model with Matlab</a></div></div><div class="u-pb4x u-mt3x"><div class="summary u-fs14 u-fw300 u-lineHeight1_5 u-tcGrayDarkest"><div class="summarized">We use the framework implicit in the model of inflation by Shone (1997) to address the analytical properties of a simple dynamic aggregate supply and aggregate demand (AS-AD) model and solve it numerically. The model undergoes a... <a class="more_link u-tcGrayDark u-linkUnstyled" data-container=".work_68296346" data-show=".complete" data-hide=".summarized" data-more-link-behavior="true" href="#">more</a></div><div class="complete hidden">We use the framework implicit in the model of inflation by Shone (1997) to address the analytical properties of a simple dynamic aggregate supply and aggregate demand (AS-AD) model and solve it numerically. The model undergoes a bifurcation as its steady state smoothly interchanges stability depending on the relation between the sensitivity of the demand for liquidity to variations in the interest rate and the way expectations on inflation are formed based on real output fluctuations. Using code embedded into a unique function in Matlab, we plot the numerical solutions of the model and simulate different dynamic adjustments using different parameter values. The same function also accommodates for the implementation of different policy shocks: monetary policy shocks through changes in the growth rate of money supply, fiscal policy shocks due to variations in public spending and in the exogenous tax rate, and supply side shocks as given by changes in the level of natural output.</div></div></div><ul class="InlineList u-ph0x u-fs13"><li class="InlineList-item logged_in_only"><div class="share_on_academia_work_button"><a class="academia_share Button Button--inverseBlue Button--sm js-bookmark-button" data-academia-share="Work/68296346" data-share-source="work_strip" data-spinner="small_white_hide_contents"><i class="fa fa-plus"></i><span class="work-strip-link-text u-ml1x" data-content="button_text">Bookmark</span></a></div></li><li class="InlineList-item"><div class="download"><a id="936cb487f2aed6986e6007765c04884b" rel="nofollow" data-download="{"attachment_id":78821705,"asset_id":68296346,"asset_type":"Work","always_allow_download":false,"track":null,"button_location":"work_strip","source":null,"hide_modal":null}" class="Button Button--sm Button--inverseGreen js-download-button prompt_button doc_download" href="https://www.academia.edu/attachments/78821705/download_file?st=MTc0MDU1NDU5OCw4LjIyMi4yMDguMTQ2&s=work_strip"><i class="fa fa-arrow-circle-o-down fa-lg"></i><span class="u-textUppercase u-ml1x" data-content="button_text">Download</span></a></div></li><li class="InlineList-item"><ul class="InlineList InlineList--bordered u-ph0x"><li class="InlineList-item InlineList-item--bordered"><span class="InlineList-item-text">by <span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a class="u-tcGrayDark u-fw700" data-has-card-for-user="1946622" href="https://up-pt.academia.edu/Jos%C3%A9Gaspar">José M . Gaspar</a><script data-card-contents-for-user="1946622" type="text/json">{"id":1946622,"first_name":"José","last_name":"Gaspar","domain_name":"up-pt","page_name":"JoséGaspar","display_name":"José M . Gaspar","profile_url":"https://up-pt.academia.edu/Jos%C3%A9Gaspar?f_ri=725","photo":"https://0.academia-photos.com/1946622/688824/23568884/s65_jos_.gaspar.jpg"}</script></span></span></li><li class="js-paper-rank-work_68296346 InlineList-item InlineList-item--bordered hidden"><span class="js-paper-rank-view hidden u-tcGrayDark" data-paper-rank-work-id="68296346"><i class="u-m1x fa fa-bar-chart"></i><strong class="js-paper-rank"></strong></span><script>$(function() { new Works.PaperRankView({ workId: 68296346, container: ".js-paper-rank-work_68296346", }); });</script></li><li class="js-percentile-work_68296346 InlineList-item InlineList-item--bordered hidden u-tcGrayDark"><span class="percentile-widget hidden"><span class="u-mr2x percentile-widget" style="display: none">•</span><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 68296346; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-percentile-work_68296346"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></li><li class="js-view-count-work_68296346 InlineList-item InlineList-item--bordered hidden"><div><span><span class="js-view-count view-count u-mr2x" data-work-id="68296346"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 68296346; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=68296346]").text(description); $(".js-view-count-work_68296346").attr('title', description).tooltip(); }); });</script></span><script>$(function() { $(".js-view-count-work_68296346").removeClass('hidden') })</script></div></li><li class="InlineList-item u-positionRelative" style="max-width: 250px"><div class="u-positionAbsolute" data-has-card-for-ri-list="68296346"><i class="fa fa-tag InlineList-item-icon u-positionRelative"></i>  <a class="InlineList-item-text u-positionRelative">5</a>  </div><span class="InlineList-item-text u-textTruncate u-pl9x"><a class="InlineList-item-text" data-has-card-for-ri="724" rel="nofollow" href="https://www.academia.edu/Documents/in/Economics">Economics</a>, <script data-card-contents-for-ri="724" type="text/json">{"id":724,"name":"Economics","url":"https://www.academia.edu/Documents/in/Economics?f_ri=725","nofollow":true}</script><a class="InlineList-item-text" data-has-card-for-ri="725" rel="nofollow" href="https://www.academia.edu/Documents/in/Computational_Economics">Computational Economics</a>, <script data-card-contents-for-ri="725" type="text/json">{"id":725,"name":"Computational Economics","url":"https://www.academia.edu/Documents/in/Computational_Economics?f_ri=725","nofollow":true}</script><a class="InlineList-item-text" data-has-card-for-ri="764" rel="nofollow" href="https://www.academia.edu/Documents/in/Macroeconomics">Macroeconomics</a>, <script data-card-contents-for-ri="764" type="text/json">{"id":764,"name":"Macroeconomics","url":"https://www.academia.edu/Documents/in/Macroeconomics?f_ri=725","nofollow":true}</script><a class="InlineList-item-text" data-has-card-for-ri="25395" rel="nofollow" href="https://www.academia.edu/Documents/in/Matlab">Matlab</a><script data-card-contents-for-ri="25395" type="text/json">{"id":25395,"name":"Matlab","url":"https://www.academia.edu/Documents/in/Matlab?f_ri=725","nofollow":true}</script></span></li><script>(function(){ if (true) { new Aedu.ResearchInterestListCard({ el: $('*[data-has-card-for-ri-list=68296346]'), work: {"id":68296346,"title":"A dynamic aggregate supply and aggregate demand model with Matlab","created_at":"2022-01-15T08:22:40.544-08:00","url":"https://www.academia.edu/68296346/A_dynamic_aggregate_supply_and_aggregate_demand_model_with_Matlab?f_ri=725","dom_id":"work_68296346","summary":"We use the framework implicit in the model of inflation by Shone (1997) to address the analytical properties of a simple dynamic aggregate supply and aggregate demand (AS-AD) model and solve it numerically. The model undergoes a bifurcation as its steady state smoothly interchanges stability depending on the relation between the sensitivity of the demand for liquidity to variations in the interest rate and the way expectations on inflation are formed based on real output fluctuations. Using code embedded into a unique function in Matlab, we plot the numerical solutions of the model and simulate different dynamic adjustments using different parameter values. The same function also accommodates for the implementation of different policy shocks: monetary policy shocks through changes in the growth rate of money supply, fiscal policy shocks due to variations in public spending and in the exogenous tax rate, and supply side shocks as given by changes in the level of natural output.","downloadable_attachments":[{"id":78821705,"asset_id":68296346,"asset_type":"Work","always_allow_download":false}],"ordered_authors":[{"id":1946622,"first_name":"José","last_name":"Gaspar","domain_name":"up-pt","page_name":"JoséGaspar","display_name":"José M . Gaspar","profile_url":"https://up-pt.academia.edu/Jos%C3%A9Gaspar?f_ri=725","photo":"https://0.academia-photos.com/1946622/688824/23568884/s65_jos_.gaspar.jpg"}],"research_interests":[{"id":724,"name":"Economics","url":"https://www.academia.edu/Documents/in/Economics?f_ri=725","nofollow":true},{"id":725,"name":"Computational Economics","url":"https://www.academia.edu/Documents/in/Computational_Economics?f_ri=725","nofollow":true},{"id":764,"name":"Macroeconomics","url":"https://www.academia.edu/Documents/in/Macroeconomics?f_ri=725","nofollow":true},{"id":25395,"name":"Matlab","url":"https://www.academia.edu/Documents/in/Matlab?f_ri=725","nofollow":true},{"id":367028,"name":"Business Cycles","url":"https://www.academia.edu/Documents/in/Business_Cycles?f_ri=725"}]}, }) } })();</script></ul></li></ul></div></div><div class="u-borderBottom1 u-borderColorGrayLighter"><div class="clearfix u-pv7x u-mb0x js-work-card work_18721118 coauthored" data-work_id="18721118" itemscope="itemscope" itemtype="https://schema.org/ScholarlyArticle"><div class="header"><div class="title u-fontSerif u-fs22 u-lineHeight1_3"><a class="u-tcGrayDarkest js-work-link" href="https://www.academia.edu/18721118/Tracing_the_temporal_evolution_of_clusters_in_a_financial_stock_market">Tracing the temporal evolution of clusters in a financial stock market</a></div></div><div class="u-pb4x u-mt3x"><div class="summary u-fs14 u-fw300 u-lineHeight1_5 u-tcGrayDarkest"><div class="summarized">We propose a methodology for clustering financial time series of stocks&#39; returns, and a graphical set-up to quantify and visualise the evolution of these clusters through time. The proposed graphical representation allows for the... <a class="more_link u-tcGrayDark u-linkUnstyled" data-container=".work_18721118" data-show=".complete" data-hide=".summarized" data-more-link-behavior="true" href="#">more</a></div><div class="complete hidden">We propose a methodology for clustering financial time series of stocks&#39; returns, and a graphical set-up to quantify and visualise the evolution of these clusters through time. The proposed graphical representation allows for the application of well known algorithms for solving classical combinatorial graph problems, which can be interpreted as problems relevant to portfolio design and investment strategies. We illustrate</div></div></div><ul class="InlineList u-ph0x u-fs13"><li class="InlineList-item logged_in_only"><div class="share_on_academia_work_button"><a class="academia_share Button Button--inverseBlue Button--sm js-bookmark-button" data-academia-share="Work/18721118" data-share-source="work_strip" data-spinner="small_white_hide_contents"><i class="fa fa-plus"></i><span class="work-strip-link-text u-ml1x" data-content="button_text">Bookmark</span></a></div></li><li class="InlineList-item"><div class="download"><a id="6e5a3a12e76d3979ad77157192a1c53c" rel="nofollow" data-download="{"attachment_id":40219082,"asset_id":18721118,"asset_type":"Work","always_allow_download":false,"track":null,"button_location":"work_strip","source":null,"hide_modal":null}" class="Button Button--sm Button--inverseGreen js-download-button prompt_button doc_download" href="https://www.academia.edu/attachments/40219082/download_file?st=MTc0MDU1NDU5OCw4LjIyMi4yMDguMTQ2&s=work_strip"><i class="fa fa-arrow-circle-o-down fa-lg"></i><span class="u-textUppercase u-ml1x" data-content="button_text">Download</span></a></div></li><li class="InlineList-item"><ul class="InlineList InlineList--bordered u-ph0x"><li class="InlineList-item InlineList-item--bordered"><span class="InlineList-item-text">by <span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a class="u-tcGrayDark u-fw700" data-has-card-for-user="38788733" href="https://independent.academia.edu/AlejandraCaba%C3%B1a">Alejandra Cabaña</a><script data-card-contents-for-user="38788733" type="text/json">{"id":38788733,"first_name":"Alejandra","last_name":"Cabaña","domain_name":"independent","page_name":"AlejandraCabaña","display_name":"Alejandra Cabaña","profile_url":"https://independent.academia.edu/AlejandraCaba%C3%B1a?f_ri=725","photo":"https://0.academia-photos.com/38788733/137242333/126701778/s65_alejandra.caba_a.jpeg"}</script></span></span><span class="u-displayInlineBlock InlineList-item-text"> and <span class="u-textDecorationUnderline u-clickable InlineList-item-text js-work-more-authors-18721118">+1</span><div class="hidden js-additional-users-18721118"><div><span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a href="https://independent.academia.edu/ArgimiroArratia">Argimiro Arratia</a></span></div></div></span><script>(function(){ var popoverSettings = { el: $('.js-work-more-authors-18721118'), placement: 'bottom', hide_delay: 200, html: true, content: function(){ return $('.js-additional-users-18721118').html(); } } new HoverPopover(popoverSettings); })();</script></li><li class="js-paper-rank-work_18721118 InlineList-item InlineList-item--bordered hidden"><span class="js-paper-rank-view hidden u-tcGrayDark" data-paper-rank-work-id="18721118"><i class="u-m1x fa fa-bar-chart"></i><strong class="js-paper-rank"></strong></span><script>$(function() { new Works.PaperRankView({ workId: 18721118, container: ".js-paper-rank-work_18721118", }); });</script></li><li class="js-percentile-work_18721118 InlineList-item InlineList-item--bordered hidden u-tcGrayDark"><span class="percentile-widget hidden"><span class="u-mr2x percentile-widget" style="display: none">•</span><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 18721118; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-percentile-work_18721118"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></li><li class="js-view-count-work_18721118 InlineList-item InlineList-item--bordered hidden"><div><span><span class="js-view-count view-count u-mr2x" data-work-id="18721118"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 18721118; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=18721118]").text(description); $(".js-view-count-work_18721118").attr('title', description).tooltip(); }); });</script></span><script>$(function() { $(".js-view-count-work_18721118").removeClass('hidden') })</script></div></li><li class="InlineList-item u-positionRelative" style="max-width: 250px"><div class="u-positionAbsolute" data-has-card-for-ri-list="18721118"><i class="fa fa-tag InlineList-item-icon u-positionRelative"></i>  <a class="InlineList-item-text u-positionRelative">8</a>  </div><span class="InlineList-item-text u-textTruncate u-pl9x"><a class="InlineList-item-text" data-has-card-for-ri="725" rel="nofollow" href="https://www.academia.edu/Documents/in/Computational_Economics">Computational Economics</a>, <script data-card-contents-for-ri="725" type="text/json">{"id":725,"name":"Computational Economics","url":"https://www.academia.edu/Documents/in/Computational_Economics?f_ri=725","nofollow":true}</script><a class="InlineList-item-text" data-has-card-for-ri="747" rel="nofollow" href="https://www.academia.edu/Documents/in/Econometrics">Econometrics</a>, <script data-card-contents-for-ri="747" type="text/json">{"id":747,"name":"Econometrics","url":"https://www.academia.edu/Documents/in/Econometrics?f_ri=725","nofollow":true}</script><a class="InlineList-item-text" data-has-card-for-ri="29156" rel="nofollow" href="https://www.academia.edu/Documents/in/Stock_Market">Stock Market</a>, <script data-card-contents-for-ri="29156" type="text/json">{"id":29156,"name":"Stock Market","url":"https://www.academia.edu/Documents/in/Stock_Market?f_ri=725","nofollow":true}</script><a class="InlineList-item-text" data-has-card-for-ri="61227" rel="nofollow" href="https://www.academia.edu/Documents/in/Financial_time_series">Financial time series</a><script data-card-contents-for-ri="61227" type="text/json">{"id":61227,"name":"Financial time series","url":"https://www.academia.edu/Documents/in/Financial_time_series?f_ri=725","nofollow":true}</script></span></li><script>(function(){ if (true) { new Aedu.ResearchInterestListCard({ el: $('*[data-has-card-for-ri-list=18721118]'), work: {"id":18721118,"title":"Tracing the temporal evolution of clusters in a financial stock market","created_at":"2015-11-20T12:40:09.236-08:00","url":"https://www.academia.edu/18721118/Tracing_the_temporal_evolution_of_clusters_in_a_financial_stock_market?f_ri=725","dom_id":"work_18721118","summary":"We propose a methodology for clustering financial time series of stocks\u0026#39; returns, and a graphical set-up to quantify and visualise the evolution of these clusters through time. The proposed graphical representation allows for the application of well known algorithms for solving classical combinatorial graph problems, which can be interpreted as problems relevant to portfolio design and investment strategies. We illustrate","downloadable_attachments":[{"id":40219082,"asset_id":18721118,"asset_type":"Work","always_allow_download":false}],"ordered_authors":[{"id":38788733,"first_name":"Alejandra","last_name":"Cabaña","domain_name":"independent","page_name":"AlejandraCabaña","display_name":"Alejandra Cabaña","profile_url":"https://independent.academia.edu/AlejandraCaba%C3%B1a?f_ri=725","photo":"https://0.academia-photos.com/38788733/137242333/126701778/s65_alejandra.caba_a.jpeg"},{"id":39197368,"first_name":"Argimiro","last_name":"Arratia","domain_name":"independent","page_name":"ArgimiroArratia","display_name":"Argimiro Arratia","profile_url":"https://independent.academia.edu/ArgimiroArratia?f_ri=725","photo":"/images/s65_no_pic.png"}],"research_interests":[{"id":725,"name":"Computational Economics","url":"https://www.academia.edu/Documents/in/Computational_Economics?f_ri=725","nofollow":true},{"id":747,"name":"Econometrics","url":"https://www.academia.edu/Documents/in/Econometrics?f_ri=725","nofollow":true},{"id":29156,"name":"Stock Market","url":"https://www.academia.edu/Documents/in/Stock_Market?f_ri=725","nofollow":true},{"id":61227,"name":"Financial time series","url":"https://www.academia.edu/Documents/in/Financial_time_series?f_ri=725","nofollow":true},{"id":161591,"name":"Graph Representation","url":"https://www.academia.edu/Documents/in/Graph_Representation?f_ri=725"},{"id":311931,"name":"STOCK EXCHANGE","url":"https://www.academia.edu/Documents/in/STOCK_EXCHANGE?f_ri=725"},{"id":639625,"name":"Investment Strategies","url":"https://www.academia.edu/Documents/in/Investment_Strategies?f_ri=725"},{"id":1011634,"name":"Graphical Representation","url":"https://www.academia.edu/Documents/in/Graphical_Representation?f_ri=725"}]}, }) } })();</script></ul></li></ul></div></div><div class="u-borderBottom1 u-borderColorGrayLighter"><div class="clearfix u-pv7x u-mb0x js-work-card work_66761391" data-work_id="66761391" itemscope="itemscope" itemtype="https://schema.org/ScholarlyArticle"><div class="header"><div class="title u-fontSerif u-fs22 u-lineHeight1_3"><a class="u-tcGrayDarkest js-work-link" href="https://www.academia.edu/66761391/Computation_in_Economics">Computation in Economics</a></div></div><div class="u-pb4x u-mt3x"><div class="summary u-fs14 u-fw300 u-lineHeight1_5 u-tcGrayDarkest"><div class="summarized">This is an attempt at a succinct survey, from methodological and epistemological perspectives, of the burgeoning, apparently unstructured, field of what is often – misleadingly – referred to as computational economics. We identify and... <a class="more_link u-tcGrayDark u-linkUnstyled" data-container=".work_66761391" data-show=".complete" data-hide=".summarized" data-more-link-behavior="true" href="#">more</a></div><div class="complete hidden">This is an attempt at a succinct survey, from methodological and epistemological perspectives, of the burgeoning, apparently unstructured, field of what is often – misleadingly – referred to as computational economics. We identify and characterise four frontier research fields, encompassing both micro and macro aspects of economic theory, where machine computation play crucial roles in formal modelling exercises: algorithmic behavioural economics, computable general equilibrium theory, agent based computational economics and computable economics. In some senses these four research frontiers raise, without resolving, many interesting methodological and epistemological issues in economic theorising in (alternative) mathematical modes</div></div></div><ul class="InlineList u-ph0x u-fs13"><li class="InlineList-item logged_in_only"><div class="share_on_academia_work_button"><a class="academia_share Button Button--inverseBlue Button--sm js-bookmark-button" data-academia-share="Work/66761391" data-share-source="work_strip" data-spinner="small_white_hide_contents"><i class="fa fa-plus"></i><span class="work-strip-link-text u-ml1x" data-content="button_text">Bookmark</span></a></div></li><li class="InlineList-item"><div class="download"><a id="0da05a59b87743009c8694ea6dfa56c6" rel="nofollow" data-download="{"attachment_id":77828428,"asset_id":66761391,"asset_type":"Work","always_allow_download":false,"track":null,"button_location":"work_strip","source":null,"hide_modal":null}" class="Button Button--sm Button--inverseGreen js-download-button prompt_button doc_download" href="https://www.academia.edu/attachments/77828428/download_file?st=MTc0MDU1NDU5OCw4LjIyMi4yMDguMTQ2&s=work_strip"><i class="fa fa-arrow-circle-o-down fa-lg"></i><span class="u-textUppercase u-ml1x" data-content="button_text">Download</span></a></div></li><li class="InlineList-item"><ul class="InlineList InlineList--bordered u-ph0x"><li class="InlineList-item InlineList-item--bordered"><span class="InlineList-item-text">by <span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a class="u-tcGrayDark u-fw700" data-has-card-for-user="190616897" href="https://independent.academia.edu/StefanoZambelli3">Stefano Zambelli</a><script data-card-contents-for-user="190616897" type="text/json">{"id":190616897,"first_name":"Stefano","last_name":"Zambelli","domain_name":"independent","page_name":"StefanoZambelli3","display_name":"Stefano Zambelli","profile_url":"https://independent.academia.edu/StefanoZambelli3?f_ri=725","photo":"https://0.academia-photos.com/190616897/53854190/41988031/s65_stefano.zambelli.png"}</script></span></span></li><li class="js-paper-rank-work_66761391 InlineList-item InlineList-item--bordered hidden"><span class="js-paper-rank-view hidden u-tcGrayDark" data-paper-rank-work-id="66761391"><i class="u-m1x fa fa-bar-chart"></i><strong class="js-paper-rank"></strong></span><script>$(function() { new Works.PaperRankView({ workId: 66761391, container: ".js-paper-rank-work_66761391", }); 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$(".js-view-count[data-work-id=66761391]").text(description); $(".js-view-count-work_66761391").attr('title', description).tooltip(); }); });</script></span><script>$(function() { $(".js-view-count-work_66761391").removeClass('hidden') })</script></div></li><li class="InlineList-item u-positionRelative" style="max-width: 250px"><div class="u-positionAbsolute" data-has-card-for-ri-list="66761391"><i class="fa fa-tag InlineList-item-icon u-positionRelative"></i>  <a class="InlineList-item-text u-positionRelative">8</a>  </div><span class="InlineList-item-text u-textTruncate u-pl9x"><a class="InlineList-item-text" data-has-card-for-ri="724" rel="nofollow" href="https://www.academia.edu/Documents/in/Economics">Economics</a>, <script data-card-contents-for-ri="724" type="text/json">{"id":724,"name":"Economics","url":"https://www.academia.edu/Documents/in/Economics?f_ri=725","nofollow":true}</script><a class="InlineList-item-text" data-has-card-for-ri="725" rel="nofollow" href="https://www.academia.edu/Documents/in/Computational_Economics">Computational Economics</a>, <script data-card-contents-for-ri="725" type="text/json">{"id":725,"name":"Computational Economics","url":"https://www.academia.edu/Documents/in/Computational_Economics?f_ri=725","nofollow":true}</script><a class="InlineList-item-text" data-has-card-for-ri="6208" rel="nofollow" href="https://www.academia.edu/Documents/in/Economic_Theory">Economic Theory</a>, <script data-card-contents-for-ri="6208" type="text/json">{"id":6208,"name":"Economic Theory","url":"https://www.academia.edu/Documents/in/Economic_Theory?f_ri=725","nofollow":true}</script><a class="InlineList-item-text" data-has-card-for-ri="7406" rel="nofollow" href="https://www.academia.edu/Documents/in/Agent_Based">Agent Based</a><script data-card-contents-for-ri="7406" type="text/json">{"id":7406,"name":"Agent Based","url":"https://www.academia.edu/Documents/in/Agent_Based?f_ri=725","nofollow":true}</script></span></li><script>(function(){ if (true) { new Aedu.ResearchInterestListCard({ el: $('*[data-has-card-for-ri-list=66761391]'), work: {"id":66761391,"title":"Computation in Economics","created_at":"2021-12-31T23:52:03.683-08:00","url":"https://www.academia.edu/66761391/Computation_in_Economics?f_ri=725","dom_id":"work_66761391","summary":"This is an attempt at a succinct survey, from methodological and epistemological perspectives, of the burgeoning, apparently unstructured, field of what is often – misleadingly – referred to as computational economics. We identify and characterise four frontier research fields, encompassing both micro and macro aspects of economic theory, where machine computation play crucial roles in formal modelling exercises: algorithmic behavioural economics, computable general equilibrium theory, agent based computational economics and computable economics. In some senses these four research frontiers raise, without resolving, many interesting methodological and epistemological issues in economic theorising in (alternative) mathematical modes","downloadable_attachments":[{"id":77828428,"asset_id":66761391,"asset_type":"Work","always_allow_download":false}],"ordered_authors":[{"id":190616897,"first_name":"Stefano","last_name":"Zambelli","domain_name":"independent","page_name":"StefanoZambelli3","display_name":"Stefano Zambelli","profile_url":"https://independent.academia.edu/StefanoZambelli3?f_ri=725","photo":"https://0.academia-photos.com/190616897/53854190/41988031/s65_stefano.zambelli.png"}],"research_interests":[{"id":724,"name":"Economics","url":"https://www.academia.edu/Documents/in/Economics?f_ri=725","nofollow":true},{"id":725,"name":"Computational Economics","url":"https://www.academia.edu/Documents/in/Computational_Economics?f_ri=725","nofollow":true},{"id":6208,"name":"Economic Theory","url":"https://www.academia.edu/Documents/in/Economic_Theory?f_ri=725","nofollow":true},{"id":7406,"name":"Agent Based","url":"https://www.academia.edu/Documents/in/Agent_Based?f_ri=725","nofollow":true},{"id":12022,"name":"Numerical Analysis","url":"https://www.academia.edu/Documents/in/Numerical_Analysis?f_ri=725"},{"id":79158,"name":"Computable General Equilibrium","url":"https://www.academia.edu/Documents/in/Computable_General_Equilibrium?f_ri=725"},{"id":925792,"name":"Computability","url":"https://www.academia.edu/Documents/in/Computability?f_ri=725"},{"id":1226770,"name":"Behavioural Economics","url":"https://www.academia.edu/Documents/in/Behavioural_Economics?f_ri=725"}]}, }) } })();</script></ul></li></ul></div></div><div class="u-borderBottom1 u-borderColorGrayLighter"><div class="clearfix u-pv7x u-mb0x js-work-card work_55914414" data-work_id="55914414" itemscope="itemscope" itemtype="https://schema.org/ScholarlyArticle"><div class="header"><div class="title u-fontSerif u-fs22 u-lineHeight1_3"><a class="u-tcGrayDarkest js-work-link" href="https://www.academia.edu/55914414/Robust_Artificial_Neural_Networks_for_Pricing_of_European_Options">Robust Artificial Neural Networks for Pricing of European Options</a></div></div><div class="u-pb4x u-mt3x"><div class="summary u-fs14 u-fw300 u-lineHeight1_5 u-tcGrayDarkest"><div class="summarized">The option pricing ability of Robust Artificial Neural Networks optimized with the Huber function is compared against those optimized with Least Squares. Comparison is in respect to pricing European call options on the S&P 500 using daily... <a class="more_link u-tcGrayDark u-linkUnstyled" data-container=".work_55914414" data-show=".complete" data-hide=".summarized" data-more-link-behavior="true" href="#">more</a></div><div class="complete hidden">The option pricing ability of Robust Artificial Neural Networks optimized with the Huber function is compared against those optimized with Least Squares. Comparison is in respect to pricing European call options on the S&P 500 using daily data for the period April 1998 to August 2001. The analysis is augmented with the use of several historical and implied volatility measures. Implied volatilities are the overall average, and the average per maturity. Beyond the standard neural networks, hybrid networks that directly incorporate information from the parametric model are included in the analysis. It is shown that the artificial neural network models with the use of the Huber function outperform the ones optimized with least squares.</div></div></div><ul class="InlineList u-ph0x u-fs13"><li class="InlineList-item logged_in_only"><div class="share_on_academia_work_button"><a class="academia_share Button Button--inverseBlue Button--sm js-bookmark-button" data-academia-share="Work/55914414" data-share-source="work_strip" data-spinner="small_white_hide_contents"><i class="fa fa-plus"></i><span class="work-strip-link-text u-ml1x" data-content="button_text">Bookmark</span></a></div></li><li class="InlineList-item"><div class="download"><a id="1d30f4c67b717792a9c5e7a47989bf7b" rel="nofollow" data-download="{"attachment_id":71558046,"asset_id":55914414,"asset_type":"Work","always_allow_download":false,"track":null,"button_location":"work_strip","source":null,"hide_modal":null}" class="Button Button--sm Button--inverseGreen js-download-button prompt_button doc_download" href="https://www.academia.edu/attachments/71558046/download_file?st=MTc0MDU1NDU5OCw4LjIyMi4yMDguMTQ2&s=work_strip"><i class="fa fa-arrow-circle-o-down fa-lg"></i><span class="u-textUppercase u-ml1x" data-content="button_text">Download</span></a></div></li><li class="InlineList-item"><ul class="InlineList InlineList--bordered u-ph0x"><li class="InlineList-item InlineList-item--bordered"><span class="InlineList-item-text">by <span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a class="u-tcGrayDark u-fw700" data-has-card-for-user="125973451" href="https://cut.academia.edu/PanayiotisAndreou">Panayiotis Andreou</a><script data-card-contents-for-user="125973451" type="text/json">{"id":125973451,"first_name":"Panayiotis","last_name":"Andreou","domain_name":"cut","page_name":"PanayiotisAndreou","display_name":"Panayiotis Andreou","profile_url":"https://cut.academia.edu/PanayiotisAndreou?f_ri=725","photo":"https://0.academia-photos.com/125973451/40368566/33085470/s65_panayiotis.andreou.jpg"}</script></span></span></li><li class="js-paper-rank-work_55914414 InlineList-item InlineList-item--bordered hidden"><span class="js-paper-rank-view hidden u-tcGrayDark" data-paper-rank-work-id="55914414"><i class="u-m1x fa fa-bar-chart"></i><strong class="js-paper-rank"></strong></span><script>$(function() { new Works.PaperRankView({ workId: 55914414, container: ".js-paper-rank-work_55914414", }); 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$(".js-view-count[data-work-id=55914414]").text(description); $(".js-view-count-work_55914414").attr('title', description).tooltip(); }); });</script></span><script>$(function() { $(".js-view-count-work_55914414").removeClass('hidden') })</script></div></li><li class="InlineList-item u-positionRelative" style="max-width: 250px"><div class="u-positionAbsolute" data-has-card-for-ri-list="55914414"><i class="fa fa-tag InlineList-item-icon u-positionRelative"></i>  <a class="InlineList-item-text u-positionRelative">10</a>  </div><span class="InlineList-item-text u-textTruncate u-pl10x"><a class="InlineList-item-text" data-has-card-for-ri="725" rel="nofollow" href="https://www.academia.edu/Documents/in/Computational_Economics">Computational Economics</a>, <script data-card-contents-for-ri="725" type="text/json">{"id":725,"name":"Computational Economics","url":"https://www.academia.edu/Documents/in/Computational_Economics?f_ri=725","nofollow":true}</script><a class="InlineList-item-text" data-has-card-for-ri="747" rel="nofollow" href="https://www.academia.edu/Documents/in/Econometrics">Econometrics</a>, <script data-card-contents-for-ri="747" type="text/json">{"id":747,"name":"Econometrics","url":"https://www.academia.edu/Documents/in/Econometrics?f_ri=725","nofollow":true}</script><a class="InlineList-item-text" data-has-card-for-ri="26066" rel="nofollow" href="https://www.academia.edu/Documents/in/Neural_Network">Neural Network</a>, <script data-card-contents-for-ri="26066" type="text/json">{"id":26066,"name":"Neural Network","url":"https://www.academia.edu/Documents/in/Neural_Network?f_ri=725","nofollow":true}</script><a class="InlineList-item-text" data-has-card-for-ri="54123" rel="nofollow" href="https://www.academia.edu/Documents/in/Artificial_Neural_Networks">Artificial Neural Networks</a><script data-card-contents-for-ri="54123" type="text/json">{"id":54123,"name":"Artificial Neural Networks","url":"https://www.academia.edu/Documents/in/Artificial_Neural_Networks?f_ri=725","nofollow":true}</script></span></li><script>(function(){ if (true) { new Aedu.ResearchInterestListCard({ el: $('*[data-has-card-for-ri-list=55914414]'), work: {"id":55914414,"title":"Robust Artificial Neural Networks for Pricing of European Options","created_at":"2021-10-06T04:40:21.538-07:00","url":"https://www.academia.edu/55914414/Robust_Artificial_Neural_Networks_for_Pricing_of_European_Options?f_ri=725","dom_id":"work_55914414","summary":"The option pricing ability of Robust Artificial Neural Networks optimized with the Huber function is compared against those optimized with Least Squares. Comparison is in respect to pricing European call options on the S\u0026P 500 using daily data for the period April 1998 to August 2001. The analysis is augmented with the use of several historical and implied volatility measures. Implied volatilities are the overall average, and the average per maturity. Beyond the standard neural networks, hybrid networks that directly incorporate information from the parametric model are included in the analysis. It is shown that the artificial neural network models with the use of the Huber function outperform the ones optimized with least squares.","downloadable_attachments":[{"id":71558046,"asset_id":55914414,"asset_type":"Work","always_allow_download":false}],"ordered_authors":[{"id":125973451,"first_name":"Panayiotis","last_name":"Andreou","domain_name":"cut","page_name":"PanayiotisAndreou","display_name":"Panayiotis Andreou","profile_url":"https://cut.academia.edu/PanayiotisAndreou?f_ri=725","photo":"https://0.academia-photos.com/125973451/40368566/33085470/s65_panayiotis.andreou.jpg"}],"research_interests":[{"id":725,"name":"Computational Economics","url":"https://www.academia.edu/Documents/in/Computational_Economics?f_ri=725","nofollow":true},{"id":747,"name":"Econometrics","url":"https://www.academia.edu/Documents/in/Econometrics?f_ri=725","nofollow":true},{"id":26066,"name":"Neural Network","url":"https://www.academia.edu/Documents/in/Neural_Network?f_ri=725","nofollow":true},{"id":54123,"name":"Artificial Neural Networks","url":"https://www.academia.edu/Documents/in/Artificial_Neural_Networks?f_ri=725","nofollow":true},{"id":601424,"name":"Option pricing","url":"https://www.academia.edu/Documents/in/Option_pricing?f_ri=725"},{"id":1114420,"name":"Implied Volatility","url":"https://www.academia.edu/Documents/in/Implied_Volatility?f_ri=725"},{"id":1211304,"name":"Artificial Neural Network","url":"https://www.academia.edu/Documents/in/Artificial_Neural_Network?f_ri=725"},{"id":2491136,"name":"Parametric Model","url":"https://www.academia.edu/Documents/in/Parametric_Model?f_ri=725"},{"id":3079415,"name":"Finance and Investment Banking","url":"https://www.academia.edu/Documents/in/Finance_and_Investment_Banking?f_ri=725"},{"id":3734593,"name":"Robust estimator","url":"https://www.academia.edu/Documents/in/Robust_estimator?f_ri=725"}]}, }) } })();</script></ul></li></ul></div></div><div class="u-borderBottom1 u-borderColorGrayLighter"><div class="clearfix u-pv7x u-mb0x js-work-card work_61228498" data-work_id="61228498" itemscope="itemscope" itemtype="https://schema.org/ScholarlyArticle"><div class="header"><div class="title u-fontSerif u-fs22 u-lineHeight1_3"><a class="u-tcGrayDarkest js-work-link" href="https://www.academia.edu/61228498/On_Optimal_design_of_treasury_bonds">On Optimal design of treasury bonds</a></div></div><div class="u-pb4x u-mt3x"><div class="summary u-fs14 u-fw300 u-lineHeight1_5 u-tcGrayDarkest"><div class="summarized">In this paper we develop a methodology for the study and the optimal design of the Italian medium, long-term Treasury securities. The aim is the determination of the optimal characteristics (coupon, maturity, etc.) of their future issues.... <a class="more_link u-tcGrayDark u-linkUnstyled" data-container=".work_61228498" data-show=".complete" data-hide=".summarized" data-more-link-behavior="true" href="#">more</a></div><div class="complete hidden">In this paper we develop a methodology for the study and the optimal design of the Italian medium, long-term Treasury securities. The aim is the determination of the optimal characteristics (coupon, maturity, etc.) of their future issues. Interest rate risk is examined in a way consistent with the issuer's perspective. When it is impossible to apply some form of duration matching to manage the net asset and the liability portfolio, the minimisation of the cost of the debt and the stability of the debt service payments could be considered as the objectives of the debt issuer. A new model is proposed for the optimal issue of interest rate sensitive securities. The model is formulated as a bilevel optimisation problem in which the issuer minimises his loss function and the investor maximises the expected utility of his portfolio.</div></div></div><ul class="InlineList u-ph0x u-fs13"><li class="InlineList-item logged_in_only"><div class="share_on_academia_work_button"><a class="academia_share Button Button--inverseBlue Button--sm js-bookmark-button" data-academia-share="Work/61228498" data-share-source="work_strip" data-spinner="small_white_hide_contents"><i class="fa fa-plus"></i><span class="work-strip-link-text u-ml1x" data-content="button_text">Bookmark</span></a></div></li><li class="InlineList-item"><div class="download"><a id="a21e8e7ab77599a192d45e1b7bad8341" rel="nofollow" data-download="{"attachment_id":74332575,"asset_id":61228498,"asset_type":"Work","always_allow_download":false,"track":null,"button_location":"work_strip","source":null,"hide_modal":null}" class="Button Button--sm Button--inverseGreen js-download-button prompt_button doc_download" href="https://www.academia.edu/attachments/74332575/download_file?st=MTc0MDU1NDU5OCw4LjIyMi4yMDguMTQ2&s=work_strip"><i class="fa fa-arrow-circle-o-down fa-lg"></i><span class="u-textUppercase u-ml1x" data-content="button_text">Download</span></a></div></li><li class="InlineList-item"><ul class="InlineList InlineList--bordered u-ph0x"><li class="InlineList-item InlineList-item--bordered"><span class="InlineList-item-text">by <span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a class="u-tcGrayDark u-fw700" data-has-card-for-user="34108297" href="https://independent.academia.edu/RosellaGiacometti">Rosella Giacometti</a><script data-card-contents-for-user="34108297" type="text/json">{"id":34108297,"first_name":"Rosella","last_name":"Giacometti","domain_name":"independent","page_name":"RosellaGiacometti","display_name":"Rosella Giacometti","profile_url":"https://independent.academia.edu/RosellaGiacometti?f_ri=725","photo":"https://0.academia-photos.com/34108297/106044741/95250651/s65_rosella.giacometti.jpeg"}</script></span></span></li><li class="js-paper-rank-work_61228498 InlineList-item InlineList-item--bordered hidden"><span class="js-paper-rank-view hidden u-tcGrayDark" data-paper-rank-work-id="61228498"><i class="u-m1x fa fa-bar-chart"></i><strong class="js-paper-rank"></strong></span><script>$(function() { new Works.PaperRankView({ workId: 61228498, container: ".js-paper-rank-work_61228498", }); 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$(".js-view-count[data-work-id=61228498]").text(description); $(".js-view-count-work_61228498").attr('title', description).tooltip(); }); });</script></span><script>$(function() { $(".js-view-count-work_61228498").removeClass('hidden') })</script></div></li><li class="InlineList-item u-positionRelative" style="max-width: 250px"><div class="u-positionAbsolute" data-has-card-for-ri-list="61228498"><i class="fa fa-tag InlineList-item-icon u-positionRelative"></i>  <a class="InlineList-item-text u-positionRelative">8</a>  </div><span class="InlineList-item-text u-textTruncate u-pl9x"><a class="InlineList-item-text" data-has-card-for-ri="725" rel="nofollow" href="https://www.academia.edu/Documents/in/Computational_Economics">Computational Economics</a>, <script data-card-contents-for-ri="725" type="text/json">{"id":725,"name":"Computational Economics","url":"https://www.academia.edu/Documents/in/Computational_Economics?f_ri=725","nofollow":true}</script><a class="InlineList-item-text" data-has-card-for-ri="747" rel="nofollow" href="https://www.academia.edu/Documents/in/Econometrics">Econometrics</a>, <script data-card-contents-for-ri="747" type="text/json">{"id":747,"name":"Econometrics","url":"https://www.academia.edu/Documents/in/Econometrics?f_ri=725","nofollow":true}</script><a class="InlineList-item-text" data-has-card-for-ri="227316" rel="nofollow" href="https://www.academia.edu/Documents/in/Expected_Utility">Expected Utility</a>, <script data-card-contents-for-ri="227316" type="text/json">{"id":227316,"name":"Expected Utility","url":"https://www.academia.edu/Documents/in/Expected_Utility?f_ri=725","nofollow":true}</script><a class="InlineList-item-text" data-has-card-for-ri="359599" rel="nofollow" href="https://www.academia.edu/Documents/in/Interest_Rate_Risk_Modeling">Interest Rate Risk Modeling</a><script data-card-contents-for-ri="359599" type="text/json">{"id":359599,"name":"Interest Rate Risk Modeling","url":"https://www.academia.edu/Documents/in/Interest_Rate_Risk_Modeling?f_ri=725","nofollow":true}</script></span></li><script>(function(){ if (true) { new Aedu.ResearchInterestListCard({ el: $('*[data-has-card-for-ri-list=61228498]'), work: {"id":61228498,"title":"On Optimal design of treasury bonds","created_at":"2021-11-07T13:18:02.339-08:00","url":"https://www.academia.edu/61228498/On_Optimal_design_of_treasury_bonds?f_ri=725","dom_id":"work_61228498","summary":"In this paper we develop a methodology for the study and the optimal design of the Italian medium, long-term Treasury securities. The aim is the determination of the optimal characteristics (coupon, maturity, etc.) of their future issues. Interest rate risk is examined in a way consistent with the issuer's perspective. When it is impossible to apply some form of duration matching to manage the net asset and the liability portfolio, the minimisation of the cost of the debt and the stability of the debt service payments could be considered as the objectives of the debt issuer. A new model is proposed for the optimal issue of interest rate sensitive securities. The model is formulated as a bilevel optimisation problem in which the issuer minimises his loss function and the investor maximises the expected utility of his portfolio.","downloadable_attachments":[{"id":74332575,"asset_id":61228498,"asset_type":"Work","always_allow_download":false}],"ordered_authors":[{"id":34108297,"first_name":"Rosella","last_name":"Giacometti","domain_name":"independent","page_name":"RosellaGiacometti","display_name":"Rosella Giacometti","profile_url":"https://independent.academia.edu/RosellaGiacometti?f_ri=725","photo":"https://0.academia-photos.com/34108297/106044741/95250651/s65_rosella.giacometti.jpeg"}],"research_interests":[{"id":725,"name":"Computational Economics","url":"https://www.academia.edu/Documents/in/Computational_Economics?f_ri=725","nofollow":true},{"id":747,"name":"Econometrics","url":"https://www.academia.edu/Documents/in/Econometrics?f_ri=725","nofollow":true},{"id":227316,"name":"Expected Utility","url":"https://www.academia.edu/Documents/in/Expected_Utility?f_ri=725","nofollow":true},{"id":359599,"name":"Interest Rate Risk Modeling","url":"https://www.academia.edu/Documents/in/Interest_Rate_Risk_Modeling?f_ri=725","nofollow":true},{"id":663534,"name":"Interest Rate","url":"https://www.academia.edu/Documents/in/Interest_Rate?f_ri=725"},{"id":789521,"name":"Optimal Design","url":"https://www.academia.edu/Documents/in/Optimal_Design?f_ri=725"},{"id":3067432,"name":"Loss function","url":"https://www.academia.edu/Documents/in/Loss_function?f_ri=725"},{"id":3079415,"name":"Finance and Investment Banking","url":"https://www.academia.edu/Documents/in/Finance_and_Investment_Banking?f_ri=725"}]}, }) } })();</script></ul></li></ul></div></div><div class="u-borderBottom1 u-borderColorGrayLighter"><div class="clearfix u-pv7x u-mb0x js-work-card work_4789209" data-work_id="4789209" itemscope="itemscope" itemtype="https://schema.org/ScholarlyArticle"><div class="header"><div class="title u-fontSerif u-fs22 u-lineHeight1_3"><a class="u-tcGrayDarkest js-work-link" href="https://www.academia.edu/4789209/Coupled_constraint_Nash_equilibria_in_environmental_games">Coupled constraint Nash equilibria in environmental games</a></div></div><div class="u-pb4x u-mt3x"><div class="summary u-fs14 u-fw300 u-lineHeight1_5 u-tcGrayDarkest"><div class="summarized">The focus of this paper is on how to model and solve an environmental compliance problem using . Existence and uniqueness of equilibrium points for concave n-person games. Econometrica 33 (3), 520-534] seminal idea of coupled constraint... <a class="more_link u-tcGrayDark u-linkUnstyled" data-container=".work_4789209" data-show=".complete" data-hide=".summarized" data-more-link-behavior="true" href="#">more</a></div><div class="complete hidden">The focus of this paper is on how to model and solve an environmental compliance problem using . Existence and uniqueness of equilibrium points for concave n-person games. Econometrica 33 (3), 520-534] seminal idea of coupled constraint equilibrium. First, Rosen's results about the existence and uniqueness of a Nash normalised equilibrium for coupled constraint games are explained. These results are then combined with a numerical approach to game solutions based on the Nikaido-Isoda function. A river basin pollution game, which is a model for a common nonpoint source pollution problem, is solved numerically using this approach. In the game, the agents face a joint constraint on the total pollution, which defines a coupled constraint set in the combined strategy space. This makes the game special in terms of the strategy spaces. Unlike for standard games where they are defined separately for each player, here we have a joint constraint on the combined strategy space of all players. Hence, the game needs coupled constraint equilibrium as the solution concept.</div></div></div><ul class="InlineList u-ph0x u-fs13"><li class="InlineList-item logged_in_only"><div class="share_on_academia_work_button"><a class="academia_share Button Button--inverseBlue Button--sm js-bookmark-button" data-academia-share="Work/4789209" data-share-source="work_strip" data-spinner="small_white_hide_contents"><i class="fa fa-plus"></i><span class="work-strip-link-text u-ml1x" data-content="button_text">Bookmark</span></a></div></li><li class="InlineList-item"><div class="download"><a id="8732b68a731010fa44641d7a73a47306" rel="nofollow" data-download="{"attachment_id":49632216,"asset_id":4789209,"asset_type":"Work","always_allow_download":false,"track":null,"button_location":"work_strip","source":null,"hide_modal":null}" class="Button Button--sm Button--inverseGreen js-download-button prompt_button doc_download" href="https://www.academia.edu/attachments/49632216/download_file?st=MTc0MDU1NDU5OCw4LjIyMi4yMDguMTQ2&s=work_strip"><i class="fa fa-arrow-circle-o-down fa-lg"></i><span class="u-textUppercase u-ml1x" data-content="button_text">Download</span></a></div></li><li class="InlineList-item"><ul class="InlineList InlineList--bordered u-ph0x"><li class="InlineList-item InlineList-item--bordered"><span class="InlineList-item-text">by <span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a class="u-tcGrayDark u-fw700" data-has-card-for-user="6178926" href="https://sydney.academia.edu/JacekKrawczyk">Jacek Krawczyk</a><script data-card-contents-for-user="6178926" type="text/json">{"id":6178926,"first_name":"Jacek","last_name":"Krawczyk","domain_name":"sydney","page_name":"JacekKrawczyk","display_name":"Jacek Krawczyk","profile_url":"https://sydney.academia.edu/JacekKrawczyk?f_ri=725","photo":"https://0.academia-photos.com/6178926/2694257/3136221/s65_jacek.krawczyk.jpg"}</script></span></span></li><li class="js-paper-rank-work_4789209 InlineList-item InlineList-item--bordered hidden"><span class="js-paper-rank-view hidden u-tcGrayDark" data-paper-rank-work-id="4789209"><i class="u-m1x fa fa-bar-chart"></i><strong class="js-paper-rank"></strong></span><script>$(function() { new Works.PaperRankView({ workId: 4789209, container: ".js-paper-rank-work_4789209", }); 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$(".js-view-count[data-work-id=4789209]").text(description); $(".js-view-count-work_4789209").attr('title', description).tooltip(); }); });</script></span><script>$(function() { $(".js-view-count-work_4789209").removeClass('hidden') })</script></div></li><li class="InlineList-item u-positionRelative" style="max-width: 250px"><div class="u-positionAbsolute" data-has-card-for-ri-list="4789209"><i class="fa fa-tag InlineList-item-icon u-positionRelative"></i>  <a class="InlineList-item-text u-positionRelative">11</a>  </div><span class="InlineList-item-text u-textTruncate u-pl10x"><a class="InlineList-item-text" data-has-card-for-ri="725" rel="nofollow" href="https://www.academia.edu/Documents/in/Computational_Economics">Computational Economics</a>, <script data-card-contents-for-ri="725" type="text/json">{"id":725,"name":"Computational Economics","url":"https://www.academia.edu/Documents/in/Computational_Economics?f_ri=725","nofollow":true}</script><a class="InlineList-item-text" data-has-card-for-ri="757" rel="nofollow" href="https://www.academia.edu/Documents/in/Game_Theory">Game Theory</a>, <script data-card-contents-for-ri="757" type="text/json">{"id":757,"name":"Game Theory","url":"https://www.academia.edu/Documents/in/Game_Theory?f_ri=725","nofollow":true}</script><a class="InlineList-item-text" data-has-card-for-ri="7609" rel="nofollow" href="https://www.academia.edu/Documents/in/Environmental_Management">Environmental Management</a>, <script data-card-contents-for-ri="7609" type="text/json">{"id":7609,"name":"Environmental Management","url":"https://www.academia.edu/Documents/in/Environmental_Management?f_ri=725","nofollow":true}</script><a class="InlineList-item-text" data-has-card-for-ri="27659" rel="nofollow" href="https://www.academia.edu/Documents/in/Applied_Economics">Applied Economics</a><script data-card-contents-for-ri="27659" type="text/json">{"id":27659,"name":"Applied Economics","url":"https://www.academia.edu/Documents/in/Applied_Economics?f_ri=725","nofollow":true}</script></span></li><script>(function(){ if (true) { new Aedu.ResearchInterestListCard({ el: $('*[data-has-card-for-ri-list=4789209]'), work: {"id":4789209,"title":"Coupled constraint Nash equilibria in environmental games","created_at":"2013-10-16T08:20:02.275-07:00","url":"https://www.academia.edu/4789209/Coupled_constraint_Nash_equilibria_in_environmental_games?f_ri=725","dom_id":"work_4789209","summary":"The focus of this paper is on how to model and solve an environmental compliance problem using . Existence and uniqueness of equilibrium points for concave n-person games. Econometrica 33 (3), 520-534] seminal idea of coupled constraint equilibrium. First, Rosen's results about the existence and uniqueness of a Nash normalised equilibrium for coupled constraint games are explained. These results are then combined with a numerical approach to game solutions based on the Nikaido-Isoda function. A river basin pollution game, which is a model for a common nonpoint source pollution problem, is solved numerically using this approach. In the game, the agents face a joint constraint on the total pollution, which defines a coupled constraint set in the combined strategy space. This makes the game special in terms of the strategy spaces. Unlike for standard games where they are defined separately for each player, here we have a joint constraint on the combined strategy space of all players. Hence, the game needs coupled constraint equilibrium as the solution concept.","downloadable_attachments":[{"id":49632216,"asset_id":4789209,"asset_type":"Work","always_allow_download":false}],"ordered_authors":[{"id":6178926,"first_name":"Jacek","last_name":"Krawczyk","domain_name":"sydney","page_name":"JacekKrawczyk","display_name":"Jacek Krawczyk","profile_url":"https://sydney.academia.edu/JacekKrawczyk?f_ri=725","photo":"https://0.academia-photos.com/6178926/2694257/3136221/s65_jacek.krawczyk.jpg"}],"research_interests":[{"id":725,"name":"Computational Economics","url":"https://www.academia.edu/Documents/in/Computational_Economics?f_ri=725","nofollow":true},{"id":757,"name":"Game Theory","url":"https://www.academia.edu/Documents/in/Game_Theory?f_ri=725","nofollow":true},{"id":7609,"name":"Environmental Management","url":"https://www.academia.edu/Documents/in/Environmental_Management?f_ri=725","nofollow":true},{"id":27659,"name":"Applied Economics","url":"https://www.academia.edu/Documents/in/Applied_Economics?f_ri=725","nofollow":true},{"id":78570,"name":"Nonpoint Source Pollution","url":"https://www.academia.edu/Documents/in/Nonpoint_Source_Pollution?f_ri=725"},{"id":88815,"name":"Legislation","url":"https://www.academia.edu/Documents/in/Legislation?f_ri=725"},{"id":177904,"name":"Nash Equilibrium","url":"https://www.academia.edu/Documents/in/Nash_Equilibrium?f_ri=725"},{"id":291498,"name":"River Basin","url":"https://www.academia.edu/Documents/in/River_Basin?f_ri=725"},{"id":824163,"name":"Non-Cooperative Game Theory","url":"https://www.academia.edu/Documents/in/Non-Cooperative_Game_Theory?f_ri=725"},{"id":1642379,"name":"Nash equilibria","url":"https://www.academia.edu/Documents/in/Nash_equilibria?f_ri=725"},{"id":1689234,"name":"Constrained Optimization","url":"https://www.academia.edu/Documents/in/Constrained_Optimization?f_ri=725"}]}, }) } })();</script></ul></li></ul></div></div><div class="u-borderBottom1 u-borderColorGrayLighter"><div class="clearfix u-pv7x u-mb0x js-work-card work_3682759" data-work_id="3682759" itemscope="itemscope" itemtype="https://schema.org/ScholarlyArticle"><div class="header"><div class="title u-fontSerif u-fs22 u-lineHeight1_3"><a class="u-tcGrayDarkest js-work-link" href="https://www.academia.edu/3682759/A_dynamic_IS_LM_Model_with_MATLAB_in_portuguese_">A dynamic IS-LM Model with MATLAB (in portuguese)</a></div></div><div class="u-pb4x u-mt3x"><div class="summary u-fs14 u-fw300 u-lineHeight1_5 u-tcGrayDarkest"><div class="summarized">Este trabalho baseia-se na implementação numérica do modelo IS-LM, um modelo académico básico da macroeconomia, cujas propriedades dinâmicas se pretende analisar através de uma função criada em Matlab para simular o modelo. Esta função... <a class="more_link u-tcGrayDark u-linkUnstyled" data-container=".work_3682759" data-show=".complete" data-hide=".summarized" data-more-link-behavior="true" href="#">more</a></div><div class="complete hidden">Este trabalho baseia-se na implementação numérica do modelo IS-LM, um modelo académico básico da macroeconomia, cujas propriedades dinâmicas se pretende analisar através de uma função criada em Matlab para simular o modelo. Esta função resolve numericamente o problema de valor inicial associado ao sistema de duas equações ordinárias lineares que traduzem a dinâmica do modelo e retorna diversos outputs, incluindo gráficos que permitem inferir sobre a estabilidade do modelo, apresentado diversas causas e indicadores. O objectivo final é que a análise do modelo por via de métodos numéricos dê resultados que sejam inteligíveis ebastante intuitivos. Grande parte da apresentação do modelo baseia-se na formulação do mesmo por Zhang (2005).</div></div></div><ul class="InlineList u-ph0x u-fs13"><li class="InlineList-item logged_in_only"><div class="share_on_academia_work_button"><a class="academia_share Button Button--inverseBlue Button--sm js-bookmark-button" data-academia-share="Work/3682759" data-share-source="work_strip" data-spinner="small_white_hide_contents"><i class="fa fa-plus"></i><span class="work-strip-link-text u-ml1x" data-content="button_text">Bookmark</span></a></div></li><li class="InlineList-item"><div class="download"><a id="cd33c2fc560c519ba79d1352dc578902" rel="nofollow" data-download="{"attachment_id":31370689,"asset_id":3682759,"asset_type":"Work","always_allow_download":false,"track":null,"button_location":"work_strip","source":null,"hide_modal":null}" class="Button Button--sm Button--inverseGreen js-download-button prompt_button doc_download" href="https://www.academia.edu/attachments/31370689/download_file?st=MTc0MDU1NDU5OCw4LjIyMi4yMDguMTQ2&s=work_strip"><i class="fa fa-arrow-circle-o-down fa-lg"></i><span class="u-textUppercase u-ml1x" data-content="button_text">Download</span></a></div></li><li class="InlineList-item"><ul class="InlineList InlineList--bordered u-ph0x"><li class="InlineList-item InlineList-item--bordered"><span class="InlineList-item-text">by <span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a class="u-tcGrayDark u-fw700" data-has-card-for-user="1946622" href="https://up-pt.academia.edu/Jos%C3%A9Gaspar">José M . Gaspar</a><script data-card-contents-for-user="1946622" type="text/json">{"id":1946622,"first_name":"José","last_name":"Gaspar","domain_name":"up-pt","page_name":"JoséGaspar","display_name":"José M . 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Esta função resolve numericamente o problema de valor inicial associado ao sistema de duas equações ordinárias lineares que traduzem a dinâmica do modelo e retorna diversos outputs, incluindo gráficos que permitem inferir sobre a estabilidade do modelo, apresentado diversas causas e indicadores. O objectivo final é que a análise do modelo por via de métodos numéricos dê resultados que sejam inteligíveis ebastante intuitivos. Grande parte da apresentação do modelo baseia-se na formulação do mesmo por Zhang (2005).","downloadable_attachments":[{"id":31370689,"asset_id":3682759,"asset_type":"Work","always_allow_download":false}],"ordered_authors":[{"id":1946622,"first_name":"José","last_name":"Gaspar","domain_name":"up-pt","page_name":"JoséGaspar","display_name":"José M . 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Traditional time series methods usually involve either the time or the frequency domain, but wavelets can combine the information from both of these. While... <a class="more_link u-tcGrayDark u-linkUnstyled" data-container=".work_32046735" data-show=".complete" data-hide=".summarized" data-more-link-behavior="true" href="#">more</a></div><div class="complete hidden">We propose a form of semi-nonparametric regression based on wavelet analysis. Traditional time series methods usually involve either the time or the frequency domain, but wavelets can combine the information from both of these. While wavelet transforms are typically restricted to equally spaced observations an integer power of 2 in number, we show how to go beyond these constraints. We use our methods to construct \patios" for 21 important international commodity price series. These graph the magnitude of the variations in the series at di erent time scales for various subperiods of the full sample.</div></div></div><ul class="InlineList u-ph0x u-fs13"><li class="InlineList-item logged_in_only"><div class="share_on_academia_work_button"><a class="academia_share Button Button--inverseBlue Button--sm js-bookmark-button" data-academia-share="Work/32046735" data-share-source="work_strip" data-spinner="small_white_hide_contents"><i class="fa fa-plus"></i><span class="work-strip-link-text u-ml1x" data-content="button_text">Bookmark</span></a></div></li><li class="InlineList-item"><div class="download"><a id="c7bb35bb2e71b7953d65f59798c948dc" rel="nofollow" data-download="{"attachment_id":52308342,"asset_id":32046735,"asset_type":"Work","always_allow_download":false,"track":null,"button_location":"work_strip","source":null,"hide_modal":null}" class="Button Button--sm Button--inverseGreen js-download-button prompt_button doc_download" href="https://www.academia.edu/attachments/52308342/download_file?st=MTc0MDU1NDU5OCw4LjIyMi4yMDguMTQ2&s=work_strip"><i class="fa fa-arrow-circle-o-down fa-lg"></i><span class="u-textUppercase u-ml1x" data-content="button_text">Download</span></a></div></li><li class="InlineList-item"><ul class="InlineList InlineList--bordered u-ph0x"><li class="InlineList-item InlineList-item--bordered"><span class="InlineList-item-text">by <span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a class="u-tcGrayDark u-fw700" data-has-card-for-user="33782563" href="https://mcgill.academia.edu/RussellDavidson">Russell Davidson</a><script data-card-contents-for-user="33782563" type="text/json">{"id":33782563,"first_name":"Russell","last_name":"Davidson","domain_name":"mcgill","page_name":"RussellDavidson","display_name":"Russell Davidson","profile_url":"https://mcgill.academia.edu/RussellDavidson?f_ri=725","photo":"https://0.academia-photos.com/33782563/46191570/35772552/s65_russell.davidson.jpeg"}</script></span></span></li><li class="js-paper-rank-work_32046735 InlineList-item InlineList-item--bordered hidden"><span class="js-paper-rank-view hidden u-tcGrayDark" data-paper-rank-work-id="32046735"><i class="u-m1x fa fa-bar-chart"></i><strong class="js-paper-rank"></strong></span><script>$(function() { new Works.PaperRankView({ workId: 32046735, container: ".js-paper-rank-work_32046735", }); 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Traditional time series methods usually involve either the time or the frequency domain, but wavelets can combine the information from both of these. While wavelet transforms are typically restricted to equally spaced observations an integer power of 2 in number, we show how to go beyond these constraints. We use our methods to construct \\patios\" for 21 important international commodity price series. These graph the magnitude of the variations in the series at di erent time scales for various subperiods of the full sample.","downloadable_attachments":[{"id":52308342,"asset_id":32046735,"asset_type":"Work","always_allow_download":false}],"ordered_authors":[{"id":33782563,"first_name":"Russell","last_name":"Davidson","domain_name":"mcgill","page_name":"RussellDavidson","display_name":"Russell Davidson","profile_url":"https://mcgill.academia.edu/RussellDavidson?f_ri=725","photo":"https://0.academia-photos.com/33782563/46191570/35772552/s65_russell.davidson.jpeg"}],"research_interests":[{"id":725,"name":"Computational Economics","url":"https://www.academia.edu/Documents/in/Computational_Economics?f_ri=725","nofollow":true},{"id":747,"name":"Econometrics","url":"https://www.academia.edu/Documents/in/Econometrics?f_ri=725","nofollow":true},{"id":4456,"name":"Time Series","url":"https://www.academia.edu/Documents/in/Time_Series?f_ri=725","nofollow":true},{"id":43974,"name":"Wavelets","url":"https://www.academia.edu/Documents/in/Wavelets?f_ri=725","nofollow":true},{"id":55276,"name":"Wavelet Analysis","url":"https://www.academia.edu/Documents/in/Wavelet_Analysis?f_ri=725"},{"id":91262,"name":"Wavelet Transform","url":"https://www.academia.edu/Documents/in/Wavelet_Transform?f_ri=725"},{"id":148990,"name":"Commodity prices","url":"https://www.academia.edu/Documents/in/Commodity_prices?f_ri=725"},{"id":180204,"name":"Nonparametric Regression","url":"https://www.academia.edu/Documents/in/Nonparametric_Regression?f_ri=725"},{"id":1625072,"name":"Frequency Domain","url":"https://www.academia.edu/Documents/in/Frequency_Domain?f_ri=725"}]}, }) } })();</script></ul></li></ul></div></div><div class="u-borderBottom1 u-borderColorGrayLighter"><div class="clearfix u-pv7x u-mb0x js-work-card work_3373342" data-work_id="3373342" itemscope="itemscope" itemtype="https://schema.org/ScholarlyArticle"><div class="header"><div class="title u-fontSerif u-fs22 u-lineHeight1_3"><a class="u-tcGrayDarkest js-work-link" href="https://www.academia.edu/3373342/A_dynamic_AS_AD_model_with_MATLAB">A dynamic AS-AD model with MATLAB</a></div></div><div class="u-pb4x u-mt3x"><div class="summary u-fs14 u-fw300 u-lineHeight1_5 u-tcGrayDarkest"><div class="summarized">I use the framework implicit in the model of inflation by Shone (1997) to address the analytical properties of a simple dynamic AS-AD model and solve it numerically. The AS-AD model is built by incorporating an expectations-augmented... <a class="more_link u-tcGrayDark u-linkUnstyled" data-container=".work_3373342" data-show=".complete" data-hide=".summarized" data-more-link-behavior="true" href="#">more</a></div><div class="complete hidden">I use the framework implicit in the model of inflation by Shone (1997) to address the analytical properties of a simple dynamic AS-AD model and solve it numerically. The AS-AD model is built by incorporating an expectations-augmented Phillips curve within an IS-LM framework. I use a program developed in MATLAB to plot the numerical solutions of the model and simulate 5 possible outcomes in terms of phase portraits using different parameter values. The same program also accommodates for the implementation of monetary policy shocks, fiscal policy shocks  and supply side shocks.</div></div></div><ul class="InlineList u-ph0x u-fs13"><li class="InlineList-item logged_in_only"><div class="share_on_academia_work_button"><a class="academia_share Button Button--inverseBlue Button--sm js-bookmark-button" data-academia-share="Work/3373342" data-share-source="work_strip" data-spinner="small_white_hide_contents"><i class="fa fa-plus"></i><span class="work-strip-link-text u-ml1x" data-content="button_text">Bookmark</span></a></div></li><li class="InlineList-item"><div class="download"><a id="6733a753dbef0af415c541f1aa0ab54d" rel="nofollow" data-download="{"attachment_id":31174594,"asset_id":3373342,"asset_type":"Work","always_allow_download":false,"track":null,"button_location":"work_strip","source":null,"hide_modal":null}" class="Button Button--sm Button--inverseGreen js-download-button prompt_button doc_download" href="https://www.academia.edu/attachments/31174594/download_file?st=MTc0MDU1NDU5OCw4LjIyMi4yMDguMTQ2&s=work_strip"><i class="fa fa-arrow-circle-o-down fa-lg"></i><span class="u-textUppercase u-ml1x" data-content="button_text">Download</span></a></div></li><li class="InlineList-item"><ul class="InlineList InlineList--bordered u-ph0x"><li class="InlineList-item InlineList-item--bordered"><span class="InlineList-item-text">by <span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a class="u-tcGrayDark u-fw700" data-has-card-for-user="1946622" href="https://up-pt.academia.edu/Jos%C3%A9Gaspar">José M . 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Gaspar","profile_url":"https://up-pt.academia.edu/Jos%C3%A9Gaspar?f_ri=725","photo":"https://0.academia-photos.com/1946622/688824/23568884/s65_jos_.gaspar.jpg"}</script></span></span></li><li class="js-paper-rank-work_3373342 InlineList-item InlineList-item--bordered hidden"><span class="js-paper-rank-view hidden u-tcGrayDark" data-paper-rank-work-id="3373342"><i class="u-m1x fa fa-bar-chart"></i><strong class="js-paper-rank"></strong></span><script>$(function() { new Works.PaperRankView({ workId: 3373342, container: ".js-paper-rank-work_3373342", }); });</script></li><li class="js-percentile-work_3373342 InlineList-item InlineList-item--bordered hidden u-tcGrayDark"><span class="percentile-widget hidden"><span class="u-mr2x percentile-widget" style="display: none">•</span><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 3373342; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-percentile-work_3373342"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></li><li class="js-view-count-work_3373342 InlineList-item InlineList-item--bordered hidden"><div><span><span class="js-view-count view-count u-mr2x" data-work-id="3373342"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 3373342; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=3373342]").text(description); $(".js-view-count-work_3373342").attr('title', description).tooltip(); }); });</script></span><script>$(function() { $(".js-view-count-work_3373342").removeClass('hidden') })</script></div></li><li class="InlineList-item u-positionRelative" style="max-width: 250px"><div class="u-positionAbsolute" data-has-card-for-ri-list="3373342"><i class="fa fa-tag InlineList-item-icon u-positionRelative"></i>  <a class="InlineList-item-text u-positionRelative">12</a>  </div><span class="InlineList-item-text u-textTruncate u-pl10x"><a class="InlineList-item-text" data-has-card-for-ri="209" rel="nofollow" href="https://www.academia.edu/Documents/in/Social_Theory">Social Theory</a>, <script data-card-contents-for-ri="209" type="text/json">{"id":209,"name":"Social Theory","url":"https://www.academia.edu/Documents/in/Social_Theory?f_ri=725","nofollow":true}</script><a class="InlineList-item-text" data-has-card-for-ri="503" rel="nofollow" href="https://www.academia.edu/Documents/in/Theoretical_Physics">Theoretical Physics</a>, <script data-card-contents-for-ri="503" type="text/json">{"id":503,"name":"Theoretical Physics","url":"https://www.academia.edu/Documents/in/Theoretical_Physics?f_ri=725","nofollow":true}</script><a class="InlineList-item-text" data-has-card-for-ri="724" rel="nofollow" href="https://www.academia.edu/Documents/in/Economics">Economics</a>, <script data-card-contents-for-ri="724" type="text/json">{"id":724,"name":"Economics","url":"https://www.academia.edu/Documents/in/Economics?f_ri=725","nofollow":true}</script><a class="InlineList-item-text" data-has-card-for-ri="725" rel="nofollow" href="https://www.academia.edu/Documents/in/Computational_Economics">Computational Economics</a><script data-card-contents-for-ri="725" type="text/json">{"id":725,"name":"Computational Economics","url":"https://www.academia.edu/Documents/in/Computational_Economics?f_ri=725","nofollow":true}</script></span></li><script>(function(){ if (true) { new Aedu.ResearchInterestListCard({ el: $('*[data-has-card-for-ri-list=3373342]'), work: {"id":3373342,"title":"A dynamic AS-AD model with MATLAB","created_at":"2013-04-23T22:55:10.001-07:00","url":"https://www.academia.edu/3373342/A_dynamic_AS_AD_model_with_MATLAB?f_ri=725","dom_id":"work_3373342","summary":"I use the framework implicit in the model of inflation by Shone (1997) to address the analytical properties of a simple dynamic AS-AD model and solve it numerically. The AS-AD model is built by incorporating an expectations-augmented Phillips curve within an IS-LM framework. I use a program developed in MATLAB to plot the numerical solutions of the model and simulate 5 possible outcomes in terms of phase portraits using different parameter values. The same program also accommodates for the implementation of monetary policy shocks, fiscal policy shocks and supply side shocks.","downloadable_attachments":[{"id":31174594,"asset_id":3373342,"asset_type":"Work","always_allow_download":false}],"ordered_authors":[{"id":1946622,"first_name":"José","last_name":"Gaspar","domain_name":"up-pt","page_name":"JoséGaspar","display_name":"José M . Gaspar","profile_url":"https://up-pt.academia.edu/Jos%C3%A9Gaspar?f_ri=725","photo":"https://0.academia-photos.com/1946622/688824/23568884/s65_jos_.gaspar.jpg"}],"research_interests":[{"id":209,"name":"Social Theory","url":"https://www.academia.edu/Documents/in/Social_Theory?f_ri=725","nofollow":true},{"id":503,"name":"Theoretical Physics","url":"https://www.academia.edu/Documents/in/Theoretical_Physics?f_ri=725","nofollow":true},{"id":724,"name":"Economics","url":"https://www.academia.edu/Documents/in/Economics?f_ri=725","nofollow":true},{"id":725,"name":"Computational Economics","url":"https://www.academia.edu/Documents/in/Computational_Economics?f_ri=725","nofollow":true},{"id":757,"name":"Game Theory","url":"https://www.academia.edu/Documents/in/Game_Theory?f_ri=725"},{"id":764,"name":"Macroeconomics","url":"https://www.academia.edu/Documents/in/Macroeconomics?f_ri=725"},{"id":7150,"name":"Complex Systems","url":"https://www.academia.edu/Documents/in/Complex_Systems?f_ri=725"},{"id":8102,"name":"Futurism","url":"https://www.academia.edu/Documents/in/Futurism?f_ri=725"},{"id":12854,"name":"Business Cycle Analysis","url":"https://www.academia.edu/Documents/in/Business_Cycle_Analysis?f_ri=725"},{"id":25395,"name":"Matlab","url":"https://www.academia.edu/Documents/in/Matlab?f_ri=725"},{"id":69676,"name":"Systems Dynamics","url":"https://www.academia.edu/Documents/in/Systems_Dynamics?f_ri=725"},{"id":972183,"name":"Macro/Micro Economics","url":"https://www.academia.edu/Documents/in/Macro_Micro_Economics?f_ri=725"}]}, }) } })();</script></ul></li></ul></div></div><div class="u-borderBottom1 u-borderColorGrayLighter"><div class="clearfix u-pv7x u-mb0x js-work-card work_17259092" data-work_id="17259092" itemscope="itemscope" itemtype="https://schema.org/ScholarlyArticle"><div class="header"><div class="title u-fontSerif u-fs22 u-lineHeight1_3"><a class="u-tcGrayDarkest js-work-link" href="https://www.academia.edu/17259092/Applied_computational_economics_and_finance">Applied computational economics and finance</a></div></div><div class="u-pb4x u-mt3x"><div class="summary u-fs14 u-fw300 u-lineHeight1_5 u-tcGrayDarkest"><div class="summarized">This is an important book that will influence future research on R&D and innovation. It brings together a number of pioneering papers by Adam Jaffe and Manuel Trajtenberg (and various co-authors) on the use of patent citations to study... <a class="more_link u-tcGrayDark u-linkUnstyled" data-container=".work_17259092" data-show=".complete" data-hide=".summarized" data-more-link-behavior="true" href="#">more</a></div><div class="complete hidden">This is an important book that will influence future research on R&D and innovation. It brings together a number of pioneering papers by Adam Jaffe and Manuel Trajtenberg (and various co-authors) on the use of patent citations to study the innovation process, plus several new pieces of work. The book is organised in four parts. The papers in Part 1 lay the 'conceptual' groundwork for research on patent citations. The first is the classic paper by Trajtenberg demonstrating that citations are linked to demand-based measures of social surplus for one important medical innovation, CT scanners. Making this link between patent citations and social (and private) value provides powerful justification for using citations in economic studies. It is surprising and unfortunate that there have not been similar studies on other innovations, despite the huge growth of empirical work on vertically differentiated product markets.</div></div></div><ul class="InlineList u-ph0x u-fs13"><li class="InlineList-item logged_in_only"><div class="share_on_academia_work_button"><a class="academia_share Button Button--inverseBlue Button--sm js-bookmark-button" data-academia-share="Work/17259092" data-share-source="work_strip" data-spinner="small_white_hide_contents"><i class="fa fa-plus"></i><span class="work-strip-link-text u-ml1x" data-content="button_text">Bookmark</span></a></div></li><li class="InlineList-item"><div class="download"><a id="6a7bb42578a303e243bbc0c228b6977a" rel="nofollow" data-download="{"attachment_id":42280425,"asset_id":17259092,"asset_type":"Work","always_allow_download":false,"track":null,"button_location":"work_strip","source":null,"hide_modal":null}" class="Button Button--sm Button--inverseGreen js-download-button prompt_button doc_download" href="https://www.academia.edu/attachments/42280425/download_file?st=MTc0MDU1NDU5OCw4LjIyMi4yMDguMTQ2&s=work_strip"><i class="fa fa-arrow-circle-o-down fa-lg"></i><span class="u-textUppercase u-ml1x" data-content="button_text">Download</span></a></div></li><li class="InlineList-item"><ul class="InlineList InlineList--bordered u-ph0x"><li class="InlineList-item InlineList-item--bordered"><span class="InlineList-item-text">by <span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a class="u-tcGrayDark u-fw700" data-has-card-for-user="36884421" href="https://independent.academia.edu/MarioMiranda35">Mario Miranda</a><script data-card-contents-for-user="36884421" type="text/json">{"id":36884421,"first_name":"Mario","last_name":"Miranda","domain_name":"independent","page_name":"MarioMiranda35","display_name":"Mario Miranda","profile_url":"https://independent.academia.edu/MarioMiranda35?f_ri=725","photo":"/images/s65_no_pic.png"}</script></span></span></li><li class="js-paper-rank-work_17259092 InlineList-item InlineList-item--bordered hidden"><span class="js-paper-rank-view hidden u-tcGrayDark" data-paper-rank-work-id="17259092"><i class="u-m1x fa fa-bar-chart"></i><strong class="js-paper-rank"></strong></span><script>$(function() { new Works.PaperRankView({ workId: 17259092, container: ".js-paper-rank-work_17259092", }); 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$(".js-view-count[data-work-id=17259092]").text(description); $(".js-view-count-work_17259092").attr('title', description).tooltip(); }); });</script></span><script>$(function() { $(".js-view-count-work_17259092").removeClass('hidden') })</script></div></li><li class="InlineList-item u-positionRelative" style="max-width: 250px"><div class="u-positionAbsolute" data-has-card-for-ri-list="17259092"><i class="fa fa-tag InlineList-item-icon u-positionRelative"></i>  <a class="InlineList-item-text u-positionRelative">13</a>  </div><span class="InlineList-item-text u-textTruncate u-pl10x"><a class="InlineList-item-text" data-has-card-for-ri="724" rel="nofollow" href="https://www.academia.edu/Documents/in/Economics">Economics</a>, <script data-card-contents-for-ri="724" type="text/json">{"id":724,"name":"Economics","url":"https://www.academia.edu/Documents/in/Economics?f_ri=725","nofollow":true}</script><a class="InlineList-item-text" data-has-card-for-ri="725" rel="nofollow" href="https://www.academia.edu/Documents/in/Computational_Economics">Computational Economics</a>, <script data-card-contents-for-ri="725" type="text/json">{"id":725,"name":"Computational Economics","url":"https://www.academia.edu/Documents/in/Computational_Economics?f_ri=725","nofollow":true}</script><a class="InlineList-item-text" data-has-card-for-ri="747" rel="nofollow" href="https://www.academia.edu/Documents/in/Econometrics">Econometrics</a>, <script data-card-contents-for-ri="747" type="text/json">{"id":747,"name":"Econometrics","url":"https://www.academia.edu/Documents/in/Econometrics?f_ri=725","nofollow":true}</script><a class="InlineList-item-text" data-has-card-for-ri="892" rel="nofollow" href="https://www.academia.edu/Documents/in/Statistics">Statistics</a><script data-card-contents-for-ri="892" type="text/json">{"id":892,"name":"Statistics","url":"https://www.academia.edu/Documents/in/Statistics?f_ri=725","nofollow":true}</script></span></li><script>(function(){ if (true) { new Aedu.ResearchInterestListCard({ el: $('*[data-has-card-for-ri-list=17259092]'), work: {"id":17259092,"title":"Applied computational economics and finance","created_at":"2015-10-24T14:35:00.876-07:00","url":"https://www.academia.edu/17259092/Applied_computational_economics_and_finance?f_ri=725","dom_id":"work_17259092","summary":"This is an important book that will influence future research on R\u0026D and innovation. It brings together a number of pioneering papers by Adam Jaffe and Manuel Trajtenberg (and various co-authors) on the use of patent citations to study the innovation process, plus several new pieces of work. The book is organised in four parts. The papers in Part 1 lay the 'conceptual' groundwork for research on patent citations. The first is the classic paper by Trajtenberg demonstrating that citations are linked to demand-based measures of social surplus for one important medical innovation, CT scanners. Making this link between patent citations and social (and private) value provides powerful justification for using citations in economic studies. It is surprising and unfortunate that there have not been similar studies on other innovations, despite the huge growth of empirical work on vertically differentiated product markets.","downloadable_attachments":[{"id":42280425,"asset_id":17259092,"asset_type":"Work","always_allow_download":false}],"ordered_authors":[{"id":36884421,"first_name":"Mario","last_name":"Miranda","domain_name":"independent","page_name":"MarioMiranda35","display_name":"Mario Miranda","profile_url":"https://independent.academia.edu/MarioMiranda35?f_ri=725","photo":"/images/s65_no_pic.png"}],"research_interests":[{"id":724,"name":"Economics","url":"https://www.academia.edu/Documents/in/Economics?f_ri=725","nofollow":true},{"id":725,"name":"Computational Economics","url":"https://www.academia.edu/Documents/in/Computational_Economics?f_ri=725","nofollow":true},{"id":747,"name":"Econometrics","url":"https://www.academia.edu/Documents/in/Econometrics?f_ri=725","nofollow":true},{"id":892,"name":"Statistics","url":"https://www.academia.edu/Documents/in/Statistics?f_ri=725","nofollow":true},{"id":32149,"name":"Numerical Method","url":"https://www.academia.edu/Documents/in/Numerical_Method?f_ri=725"},{"id":80414,"name":"Mathematical Sciences","url":"https://www.academia.edu/Documents/in/Mathematical_Sciences?f_ri=725"},{"id":171894,"name":"Computers and Mathematics with Applications 59 (2010) 35783582","url":"https://www.academia.edu/Documents/in/Computers_and_Mathematics_with_Applications_59_2010_35783582?f_ri=725"},{"id":213802,"name":"Rational Expectation","url":"https://www.academia.edu/Documents/in/Rational_Expectation?f_ri=725"},{"id":245193,"name":"Numerical Integration","url":"https://www.academia.edu/Documents/in/Numerical_Integration?f_ri=725"},{"id":506482,"name":"Function approximation","url":"https://www.academia.edu/Documents/in/Function_approximation?f_ri=725"},{"id":871199,"name":"Stochastic Model","url":"https://www.academia.edu/Documents/in/Stochastic_Model?f_ri=725"},{"id":991097,"name":"Continuous Time Systems","url":"https://www.academia.edu/Documents/in/Continuous_Time_Systems?f_ri=725"},{"id":1449632,"name":"Computational Method","url":"https://www.academia.edu/Documents/in/Computational_Method?f_ri=725"}]}, }) } })();</script></ul></li></ul></div></div><div class="u-borderBottom1 u-borderColorGrayLighter"><div class="clearfix u-pv7x u-mb0x js-work-card work_38219355" data-work_id="38219355" itemscope="itemscope" itemtype="https://schema.org/ScholarlyArticle"><div class="header"><div class="title u-fontSerif u-fs22 u-lineHeight1_3"><a class="u-tcGrayDarkest js-work-link" href="https://www.academia.edu/38219355/Lecture_notes_Computational_Methods_for_Economists_III_">Lecture notes: Computational Methods for Economists (III)</a></div></div><div class="u-pb4x u-mt3x"><div class="summary u-fs14 u-fw300 u-lineHeight1_5 u-tcGrayDarkest"><div class="summarized">In this third 'chapter' of my computational methods lecture notes we complete our discussion of dynamic / inter-temporal optimization by a discussion of using constraints and time-dependent Lagrange multipliers or 'co-stat variables'.... <a class="more_link u-tcGrayDark u-linkUnstyled" data-container=".work_38219355" data-show=".complete" data-hide=".summarized" data-more-link-behavior="true" href="#">more</a></div><div class="complete hidden">In this third 'chapter' of my computational methods lecture notes we complete our discussion of dynamic / inter-temporal optimization by a discussion of using constraints and time-dependent Lagrange multipliers or 'co-stat variables'. <br />The chapter finishes with a discussion of the second-order conditions to check whether the optimal path found represents a minimum, a maximum or a 'saddle-point' solution in the space of 'paths'. This leads us to contemplate the vector-space structure of space of functions and the use of integrals to define a dot-product on such spaces. That is the bridge to the material of next week.</div></div></div><ul class="InlineList u-ph0x u-fs13"><li class="InlineList-item logged_in_only"><div class="share_on_academia_work_button"><a class="academia_share Button Button--inverseBlue Button--sm js-bookmark-button" data-academia-share="Work/38219355" data-share-source="work_strip" data-spinner="small_white_hide_contents"><i class="fa fa-plus"></i><span class="work-strip-link-text u-ml1x" data-content="button_text">Bookmark</span></a></div></li><li class="InlineList-item"><div class="download"><a id="4323ac99221d3fc5d57bc7e4d5cd8972" rel="nofollow" data-download="{"attachment_id":58258928,"asset_id":38219355,"asset_type":"Work","always_allow_download":false,"track":null,"button_location":"work_strip","source":null,"hide_modal":null}" class="Button Button--sm Button--inverseGreen js-download-button prompt_button doc_download" href="https://www.academia.edu/attachments/58258928/download_file?st=MTc0MDU1NDU5OCw4LjIyMi4yMDguMTQ2&s=work_strip"><i class="fa fa-arrow-circle-o-down fa-lg"></i><span class="u-textUppercase u-ml1x" data-content="button_text">Download</span></a></div></li><li class="InlineList-item"><ul class="InlineList InlineList--bordered u-ph0x"><li class="InlineList-item InlineList-item--bordered"><span class="InlineList-item-text">by <span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a class="u-tcGrayDark u-fw700" data-has-card-for-user="167271" href="https://ucl.academia.edu/FrankWitte">Frank Witte</a><script data-card-contents-for-user="167271" type="text/json">{"id":167271,"first_name":"Frank","last_name":"Witte","domain_name":"ucl","page_name":"FrankWitte","display_name":"Frank Witte","profile_url":"https://ucl.academia.edu/FrankWitte?f_ri=725","photo":"https://0.academia-photos.com/167271/42301/7265266/s65_frank.witte.jpg"}</script></span></span></li><li class="js-paper-rank-work_38219355 InlineList-item InlineList-item--bordered hidden"><span class="js-paper-rank-view hidden u-tcGrayDark" data-paper-rank-work-id="38219355"><i class="u-m1x fa fa-bar-chart"></i><strong class="js-paper-rank"></strong></span><script>$(function() { new Works.PaperRankView({ workId: 38219355, container: ".js-paper-rank-work_38219355", }); 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This leads us to contemplate the vector-space structure of space of functions and the use of integrals to define a dot-product on such spaces. That is the bridge to the material of next week.","downloadable_attachments":[{"id":58258928,"asset_id":38219355,"asset_type":"Work","always_allow_download":false}],"ordered_authors":[{"id":167271,"first_name":"Frank","last_name":"Witte","domain_name":"ucl","page_name":"FrankWitte","display_name":"Frank Witte","profile_url":"https://ucl.academia.edu/FrankWitte?f_ri=725","photo":"https://0.academia-photos.com/167271/42301/7265266/s65_frank.witte.jpg"}],"research_interests":[{"id":725,"name":"Computational Economics","url":"https://www.academia.edu/Documents/in/Computational_Economics?f_ri=725","nofollow":true},{"id":749,"name":"Mathematical Economics","url":"https://www.academia.edu/Documents/in/Mathematical_Economics?f_ri=725","nofollow":true},{"id":764,"name":"Macroeconomics","url":"https://www.academia.edu/Documents/in/Macroeconomics?f_ri=725","nofollow":true},{"id":4955,"name":"Computational Modelling","url":"https://www.academia.edu/Documents/in/Computational_Modelling?f_ri=725","nofollow":true},{"id":985922,"name":"Environemntal Economics","url":"https://www.academia.edu/Documents/in/Environemntal_Economics?f_ri=725"}]}, }) } })();</script></ul></li></ul></div></div><div class="u-borderBottom1 u-borderColorGrayLighter"><div class="clearfix u-pv7x u-mb0x js-work-card work_41888316" data-work_id="41888316" itemscope="itemscope" itemtype="https://schema.org/ScholarlyArticle"><div class="header"><div class="title u-fontSerif u-fs22 u-lineHeight1_3"><a class="u-tcGrayDarkest js-work-link" href="https://www.academia.edu/41888316/How_Could_Cognitive_Revolution_Happen_To_Economics">How Could Cognitive Revolution Happen To Economics</a></div></div><div class="u-pb4x u-mt3x"><div class="summary u-fs14 u-fw300 u-lineHeight1_5 u-tcGrayDarkest"><div class="summarized">This paper introduces a highly original theory. What is human capital or knowledge theoretically? How do innovations happen? How could microeconomics integrate with macroeconomics? Where do institutions & organizations come from? How to... <a class="more_link u-tcGrayDark u-linkUnstyled" data-container=".work_41888316" data-show=".complete" data-hide=".summarized" data-more-link-behavior="true" href="#">more</a></div><div class="complete hidden">This paper introduces a highly original theory. What is human capital or knowledge theoretically? How do innovations happen? How could microeconomics integrate with macroeconomics? Where do institutions & organizations come from? How to define and endogenize money? How to synthesize irrationalities into rationalities? How to coordinate dynamics with statics (or equilibria)? Etc. All of the answers lie in the principles of computer science, which are interpreted in a distinct way transcendentally in this paper, and then reformed into a concise theory on how a person thinks. This is called the Algorithm Framework Theory, which implies the method of roundabout production of thoughts, consisting of the factors of dualism, time or speed, flows and stocks, etc. Reasoned economically, the theory surprisingly leads to pluralism, conflicts, subjectivities, irrationalities, innovations, developments, the Combinatorial Explosions and eventually an embracive paradigm of the society. This means that a unified social science and a unified economics takes shape. Also methodological synthesis is included briefly.</div></div></div><ul class="InlineList u-ph0x u-fs13"><li class="InlineList-item logged_in_only"><div class="share_on_academia_work_button"><a class="academia_share Button Button--inverseBlue Button--sm js-bookmark-button" data-academia-share="Work/41888316" data-share-source="work_strip" data-spinner="small_white_hide_contents"><i class="fa fa-plus"></i><span class="work-strip-link-text u-ml1x" data-content="button_text">Bookmark</span></a></div></li><li class="InlineList-item"><div class="download"><a id="daf6509eb5e6b1ac1727055156164ff9" rel="nofollow" data-download="{"attachment_id":62017341,"asset_id":41888316,"asset_type":"Work","always_allow_download":false,"track":null,"button_location":"work_strip","source":null,"hide_modal":null}" class="Button Button--sm Button--inverseGreen js-download-button prompt_button doc_download" href="https://www.academia.edu/attachments/62017341/download_file?st=MTc0MDU1NDU5OCw4LjIyMi4yMDguMTQ2&s=work_strip"><i class="fa fa-arrow-circle-o-down fa-lg"></i><span class="u-textUppercase u-ml1x" data-content="button_text">Download</span></a></div></li><li class="InlineList-item"><ul class="InlineList InlineList--bordered u-ph0x"><li class="InlineList-item InlineList-item--bordered"><span class="InlineList-item-text">by <span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a class="u-tcGrayDark u-fw700" data-has-card-for-user="144934071" href="https://unc.academia.edu/BinLi">Bin Li</a><script data-card-contents-for-user="144934071" type="text/json">{"id":144934071,"first_name":"Bin","last_name":"Li","domain_name":"unc","page_name":"BinLi","display_name":"Bin Li","profile_url":"https://unc.academia.edu/BinLi?f_ri=725","photo":"https://0.academia-photos.com/144934071/71202806/59642344/s65_bin.li.jpg"}</script></span></span></li><li class="js-paper-rank-work_41888316 InlineList-item InlineList-item--bordered hidden"><span class="js-paper-rank-view hidden u-tcGrayDark" data-paper-rank-work-id="41888316"><i class="u-m1x fa fa-bar-chart"></i><strong class="js-paper-rank"></strong></span><script>$(function() { new Works.PaperRankView({ workId: 41888316, container: ".js-paper-rank-work_41888316", }); 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What is human capital or knowledge theoretically? How do innovations happen? How could microeconomics integrate with macroeconomics? Where do institutions \u0026 organizations come from? How to define and endogenize money? How to synthesize irrationalities into rationalities? How to coordinate dynamics with statics (or equilibria)? Etc. All of the answers lie in the principles of computer science, which are interpreted in a distinct way transcendentally in this paper, and then reformed into a concise theory on how a person thinks. This is called the Algorithm Framework Theory, which implies the method of roundabout production of thoughts, consisting of the factors of dualism, time or speed, flows and stocks, etc. Reasoned economically, the theory surprisingly leads to pluralism, conflicts, subjectivities, irrationalities, innovations, developments, the Combinatorial Explosions and eventually an embracive paradigm of the society. This means that a unified social science and a unified economics takes shape. Also methodological synthesis is included briefly.","downloadable_attachments":[{"id":62017341,"asset_id":41888316,"asset_type":"Work","always_allow_download":false}],"ordered_authors":[{"id":144934071,"first_name":"Bin","last_name":"Li","domain_name":"unc","page_name":"BinLi","display_name":"Bin Li","profile_url":"https://unc.academia.edu/BinLi?f_ri=725","photo":"https://0.academia-photos.com/144934071/71202806/59642344/s65_bin.li.jpg"}],"research_interests":[{"id":221,"name":"Psychology","url":"https://www.academia.edu/Documents/in/Psychology?f_ri=725","nofollow":true},{"id":724,"name":"Economics","url":"https://www.academia.edu/Documents/in/Economics?f_ri=725","nofollow":true},{"id":725,"name":"Computational Economics","url":"https://www.academia.edu/Documents/in/Computational_Economics?f_ri=725","nofollow":true},{"id":803,"name":"Philosophy","url":"https://www.academia.edu/Documents/in/Philosophy?f_ri=725","nofollow":true},{"id":1237,"name":"Social Sciences","url":"https://www.academia.edu/Documents/in/Social_Sciences?f_ri=725"},{"id":55976,"name":"Cognitive economics","url":"https://www.academia.edu/Documents/in/Cognitive_economics?f_ri=725"}]}, }) } })();</script></ul></li></ul></div></div><div class="u-borderBottom1 u-borderColorGrayLighter"><div class="clearfix u-pv7x u-mb0x js-work-card work_44914442" data-work_id="44914442" itemscope="itemscope" itemtype="https://schema.org/ScholarlyArticle"><div class="header"><div class="title u-fontSerif u-fs22 u-lineHeight1_3"><a class="u-tcGrayDarkest js-work-link" href="https://www.academia.edu/44914442/A_Theory_for_Unification_of_Social_Sciences">A Theory for Unification of Social Sciences</a></div></div><div class="u-pb4x u-mt3x"><div class="summary u-fs14 u-fw300 u-lineHeight1_5 u-tcGrayDarkest"><div class="summarized">The solution to the integration of various economics and social sciences lies in the manner how a person thinks, which, illuminated by computer principles, can be interpreted dualistically and transcendentally as “thinking = computation =... <a class="more_link u-tcGrayDark u-linkUnstyled" data-container=".work_44914442" data-show=".complete" data-hide=".summarized" data-more-link-behavior="true" href="#">more</a></div><div class="complete hidden">The solution to the integration of various economics and social sciences lies in the manner how a person thinks, which, illuminated by computer principles, can be interpreted dualistically and transcendentally as “thinking = computation = (Instruction + information) × speed × time”. “Instructions” are assumed the innate and universal thinking tools that are defined definitely in computer science and numbered finitely. For example, “+”, “-“, “×”, “And”, “Or”, “Not”, “Copy”, “Compare”, “Move” are all Instructions. Different Instructions alternately and repetitively process different information or data from the spatiotemporal environment. One Instruction processes no more than two data, getting no more than one result (as “knowledge”), this is called “one operation”. Only one operation can be done in the brain at any moment, so operations have to be connected sequentially or “serially” to compute or think, and only finite number of operations can be carried out within a unit time (“limited speed”). This is called “Algorithm Framework Theory” (AFT).<br /><br />Social scientists can infer under this framework without knowing well of computer science or technological details. As the ability of an operation is so tiny, thinking or computation has to be undertaken “roundaboutly”, thereby endogenizing thinking stocks or knowledges, which both support and constrain operations, and evolve and develop qualitatively and quantitatively. Since the operations accomplished hitherto, and hence the knowledges acquired, must be limited, actors have to make decisions with the “bounded rationality”. Time and resources elapse, but the demands need to be satisfied in time, hence the decisive computations have to finish timely. This is why the tedious deductions are often “reasonably” forsaken and the actors “deductively” turn to various non-deductive methods (“Algorithms”), thereby subjectivities or “irrationalities” rationally and optimally happen. The world is pluralistic in actors’ eyes before computations, and the pluralities, via computations, diminish and converge toward consistency and equilibrium; meanwhile, with the establishment of some equilibria, human computational power is saved and therefore can be re-invest in new areas; thus, computations will return active and the world will still be pluralistic or “mixed”, where any order or regularity exists just partly. Accumulation of computational results leads to continuous knowledge expansion, innovation and development, and the mathematical principle of “Combinatorial Explosion” ensure the development would be explosive and endless, thus, the mainstream equilibrium paradigm is deconstructed, re-absorbed and broken through.<br /><br />Money arises from saving the costs of price conversion, so it is an Algorithmic consequence. Computing economy makes knowledge stocks quite rigid, which causes the endogeny of institutions as a kind of rigid knowledges. The pervasive conflicts incur waste and losses, where an organization can be built up, through buying the interpersonal obedience and concordance, to pursue the additional benefits. Governments as a kind of organization can be bred in various Algorithmic ways. Bounded rationality entails the distinction, symbiosis and overlap between intentions and consequences, which explains “Invisible Hand” as an externality. Bounded rationality also emanates that transactional opportunities are local, and then other non-transactional behaviors emerge, including the governmental and social ones.</div></div></div><ul class="InlineList u-ph0x u-fs13"><li class="InlineList-item logged_in_only"><div class="share_on_academia_work_button"><a class="academia_share Button Button--inverseBlue Button--sm js-bookmark-button" data-academia-share="Work/44914442" data-share-source="work_strip" data-spinner="small_white_hide_contents"><i class="fa fa-plus"></i><span class="work-strip-link-text u-ml1x" data-content="button_text">Bookmark</span></a></div></li><li class="InlineList-item"><div class="download"><a id="c2bb60974e10bcc4e1b9d68d4fb95782" rel="nofollow" data-download="{"attachment_id":65684175,"asset_id":44914442,"asset_type":"Work","always_allow_download":false,"track":null,"button_location":"work_strip","source":null,"hide_modal":null}" class="Button Button--sm Button--inverseGreen js-download-button prompt_button doc_download" href="https://www.academia.edu/attachments/65684175/download_file?st=MTc0MDU1NDU5OCw4LjIyMi4yMDguMTQ2&s=work_strip"><i class="fa fa-arrow-circle-o-down fa-lg"></i><span class="u-textUppercase u-ml1x" data-content="button_text">Download</span></a></div></li><li class="InlineList-item"><ul class="InlineList InlineList--bordered u-ph0x"><li class="InlineList-item InlineList-item--bordered"><span class="InlineList-item-text">by <span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a class="u-tcGrayDark u-fw700" data-has-card-for-user="144934071" href="https://unc.academia.edu/BinLi">Bin Li</a><script data-card-contents-for-user="144934071" type="text/json">{"id":144934071,"first_name":"Bin","last_name":"Li","domain_name":"unc","page_name":"BinLi","display_name":"Bin Li","profile_url":"https://unc.academia.edu/BinLi?f_ri=725","photo":"https://0.academia-photos.com/144934071/71202806/59642344/s65_bin.li.jpg"}</script></span></span></li><li class="js-paper-rank-work_44914442 InlineList-item InlineList-item--bordered hidden"><span class="js-paper-rank-view hidden u-tcGrayDark" data-paper-rank-work-id="44914442"><i class="u-m1x fa fa-bar-chart"></i><strong class="js-paper-rank"></strong></span><script>$(function() { new Works.PaperRankView({ workId: 44914442, container: ".js-paper-rank-work_44914442", }); 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For example, “+”, “-“, “×”, “And”, “Or”, “Not”, “Copy”, “Compare”, “Move” are all Instructions. Different Instructions alternately and repetitively process different information or data from the spatiotemporal environment. One Instruction processes no more than two data, getting no more than one result (as “knowledge”), this is called “one operation”. Only one operation can be done in the brain at any moment, so operations have to be connected sequentially or “serially” to compute or think, and only finite number of operations can be carried out within a unit time (“limited speed”). This is called “Algorithm Framework Theory” (AFT).\n\nSocial scientists can infer under this framework without knowing well of computer science or technological details. As the ability of an operation is so tiny, thinking or computation has to be undertaken “roundaboutly”, thereby endogenizing thinking stocks or knowledges, which both support and constrain operations, and evolve and develop qualitatively and quantitatively. Since the operations accomplished hitherto, and hence the knowledges acquired, must be limited, actors have to make decisions with the “bounded rationality”. Time and resources elapse, but the demands need to be satisfied in time, hence the decisive computations have to finish timely. This is why the tedious deductions are often “reasonably” forsaken and the actors “deductively” turn to various non-deductive methods (“Algorithms”), thereby subjectivities or “irrationalities” rationally and optimally happen. The world is pluralistic in actors’ eyes before computations, and the pluralities, via computations, diminish and converge toward consistency and equilibrium; meanwhile, with the establishment of some equilibria, human computational power is saved and therefore can be re-invest in new areas; thus, computations will return active and the world will still be pluralistic or “mixed”, where any order or regularity exists just partly. Accumulation of computational results leads to continuous knowledge expansion, innovation and development, and the mathematical principle of “Combinatorial Explosion” ensure the development would be explosive and endless, thus, the mainstream equilibrium paradigm is deconstructed, re-absorbed and broken through.\n\nMoney arises from saving the costs of price conversion, so it is an Algorithmic consequence. Computing economy makes knowledge stocks quite rigid, which causes the endogeny of institutions as a kind of rigid knowledges. The pervasive conflicts incur waste and losses, where an organization can be built up, through buying the interpersonal obedience and concordance, to pursue the additional benefits. Governments as a kind of organization can be bred in various Algorithmic ways. Bounded rationality entails the distinction, symbiosis and overlap between intentions and consequences, which explains “Invisible Hand” as an externality. Bounded rationality also emanates that transactional opportunities are local, and then other non-transactional behaviors emerge, including the governmental and social ones.","downloadable_attachments":[{"id":65684175,"asset_id":44914442,"asset_type":"Work","always_allow_download":false}],"ordered_authors":[{"id":144934071,"first_name":"Bin","last_name":"Li","domain_name":"unc","page_name":"BinLi","display_name":"Bin Li","profile_url":"https://unc.academia.edu/BinLi?f_ri=725","photo":"https://0.academia-photos.com/144934071/71202806/59642344/s65_bin.li.jpg"}],"research_interests":[{"id":184,"name":"Sociology","url":"https://www.academia.edu/Documents/in/Sociology?f_ri=725","nofollow":true},{"id":221,"name":"Psychology","url":"https://www.academia.edu/Documents/in/Psychology?f_ri=725","nofollow":true},{"id":237,"name":"Cognitive Science","url":"https://www.academia.edu/Documents/in/Cognitive_Science?f_ri=725","nofollow":true},{"id":724,"name":"Economics","url":"https://www.academia.edu/Documents/in/Economics?f_ri=725","nofollow":true},{"id":725,"name":"Computational Economics","url":"https://www.academia.edu/Documents/in/Computational_Economics?f_ri=725"},{"id":731,"name":"Evolutionary Economics","url":"https://www.academia.edu/Documents/in/Evolutionary_Economics?f_ri=725"},{"id":750,"name":"Institutional Economics","url":"https://www.academia.edu/Documents/in/Institutional_Economics?f_ri=725"},{"id":764,"name":"Macroeconomics","url":"https://www.academia.edu/Documents/in/Macroeconomics?f_ri=725"},{"id":803,"name":"Philosophy","url":"https://www.academia.edu/Documents/in/Philosophy?f_ri=725"},{"id":1237,"name":"Social Sciences","url":"https://www.academia.edu/Documents/in/Social_Sciences?f_ri=725"},{"id":2065,"name":"Research Methodology","url":"https://www.academia.edu/Documents/in/Research_Methodology?f_ri=725"},{"id":11010,"name":"Communication Theory","url":"https://www.academia.edu/Documents/in/Communication_Theory?f_ri=725"},{"id":13805,"name":"Behavioral Economics","url":"https://www.academia.edu/Documents/in/Behavioral_Economics?f_ri=725"},{"id":15708,"name":"Bounded Rationality","url":"https://www.academia.edu/Documents/in/Bounded_Rationality?f_ri=725"},{"id":56710,"name":"Social Engineering","url":"https://www.academia.edu/Documents/in/Social_Engineering?f_ri=725"},{"id":778682,"name":"New thinking in economics","url":"https://www.academia.edu/Documents/in/New_thinking_in_economics?f_ri=725"}]}, }) } })();</script></ul></li></ul></div></div><div class="u-borderBottom1 u-borderColorGrayLighter"><div class="clearfix u-pv7x u-mb0x js-work-card work_19604905" data-work_id="19604905" itemscope="itemscope" itemtype="https://schema.org/ScholarlyArticle"><div class="header"><div class="title u-fontSerif u-fs22 u-lineHeight1_3"><a class="u-tcGrayDarkest js-work-link" href="https://www.academia.edu/19604905/Accelerating_economics_how_GPUs_can_save_you_time_and_money">Accelerating economics: how GPUs can save you time and money</a></div></div><div class="u-pb4x u-mt3x"><div class="summary u-fs14 u-fw300 u-lineHeight1_5 u-tcGrayDarkest"><div class="summarized">Graphics processing units - or GPUs as they are more commonly known - are specialized circuits historically designed to efficiently handle computer graphics. They are highly parallel computers which can process large amounts of data... <a class="more_link u-tcGrayDark u-linkUnstyled" data-container=".work_19604905" data-show=".complete" data-hide=".summarized" data-more-link-behavior="true" href="#">more</a></div><div class="complete hidden">Graphics processing units - or GPUs as they are more commonly known - are specialized circuits historically designed to efficiently handle computer graphics. They are highly parallel computers which can process large amounts of data simultaneously. The graphics algorithms for which GPUs have been designed and optimized share characteristics with other algorithms used in high-performance computing. For certain well-suited scientific applications, the GPU's infrastructure has been shown to achieve substantial speedups. For example, the evaluation of the Black-Scholes partial differential equation to price financial options has been found to be performed nearly 200 times faster in parallel on a GPU than serially on a single-core CPU (Buck 2006, “GeForce 8800 & NVIDIA CUDA: A New Architecture for Computing on the GPU”).<br /><br />The main goal of this study is to illustrate how hybrid CPU/GPU systems can be used within computational economics to decrease the execution time of an implementation of a particular model. We start with a mainstream implementation of Raberto et al.'s (2001) Genoa Articial Stock Market ("GASM"), an agent-based model which simulates a financial market in discrete time in which heterogeneous agents trade a single asset. In order to ensure that it is well-suited for execution on the GPU, the algorithm used to clear the market according to the authors' specified mechanism is given a particular attention. Existing parallel programming interfaces - in particular the OpenACC standard and Thrust parallel algorithms library - are then deployed in the code. We aim to show:<br /><br />- how the codebase of our GASM implementation is adapted to utilize these technologies;<br />- how incrementally offloading work to the GPU affects the execution time of our model; <br />- how this speedup varies as a function of the problem size (e.g. number of agents, number of time steps, etc.), i.e. weak scaling; and<br />- how parameterizing the work distribution within the OpenACC programming model to increase the number of execution units used impacts this speedup, i.e. strong scaling.<br /><br />This study also aims at giving the reader a working knowledge of GPU-based parallel computing, and when and how it should be used.</div></div></div><ul class="InlineList u-ph0x u-fs13"><li class="InlineList-item logged_in_only"><div class="share_on_academia_work_button"><a class="academia_share Button Button--inverseBlue Button--sm js-bookmark-button" data-academia-share="Work/19604905" data-share-source="work_strip" data-spinner="small_white_hide_contents"><i class="fa fa-plus"></i><span class="work-strip-link-text u-ml1x" data-content="button_text">Bookmark</span></a></div></li><li class="InlineList-item"><div class="download"><a id="4a062d71d9fe41f043dc750e6f85084e" rel="nofollow" data-download="{"attachment_id":40726514,"asset_id":19604905,"asset_type":"Work","always_allow_download":false,"track":null,"button_location":"work_strip","source":null,"hide_modal":null}" class="Button Button--sm Button--inverseGreen js-download-button prompt_button doc_download" href="https://www.academia.edu/attachments/40726514/download_file?st=MTc0MDU1NDU5OCw4LjIyMi4yMDguMTQ2&s=work_strip"><i class="fa fa-arrow-circle-o-down fa-lg"></i><span class="u-textUppercase u-ml1x" data-content="button_text">Download</span></a></div></li><li class="InlineList-item"><ul class="InlineList InlineList--bordered u-ph0x"><li class="InlineList-item InlineList-item--bordered"><span class="InlineList-item-text">by <span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a class="u-tcGrayDark u-fw700" data-has-card-for-user="3947075" href="https://ethz.academia.edu/LaurentOberholzer">Laurent Oberholzer</a><script data-card-contents-for-user="3947075" type="text/json">{"id":3947075,"first_name":"Laurent","last_name":"Oberholzer","domain_name":"ethz","page_name":"LaurentOberholzer","display_name":"Laurent Oberholzer","profile_url":"https://ethz.academia.edu/LaurentOberholzer?f_ri=725","photo":"/images/s65_no_pic.png"}</script></span></span></li><li class="js-paper-rank-work_19604905 InlineList-item InlineList-item--bordered hidden"><span class="js-paper-rank-view hidden u-tcGrayDark" data-paper-rank-work-id="19604905"><i class="u-m1x fa fa-bar-chart"></i><strong class="js-paper-rank"></strong></span><script>$(function() { new Works.PaperRankView({ workId: 19604905, container: ".js-paper-rank-work_19604905", }); 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$(".js-view-count[data-work-id=19604905]").text(description); $(".js-view-count-work_19604905").attr('title', description).tooltip(); }); });</script></span><script>$(function() { $(".js-view-count-work_19604905").removeClass('hidden') })</script></div></li><li class="InlineList-item u-positionRelative" style="max-width: 250px"><div class="u-positionAbsolute" data-has-card-for-ri-list="19604905"><i class="fa fa-tag InlineList-item-icon u-positionRelative"></i>  <a class="InlineList-item-text u-positionRelative">6</a>  </div><span class="InlineList-item-text u-textTruncate u-pl9x"><a class="InlineList-item-text" data-has-card-for-ri="725" rel="nofollow" href="https://www.academia.edu/Documents/in/Computational_Economics">Computational Economics</a>, <script data-card-contents-for-ri="725" type="text/json">{"id":725,"name":"Computational Economics","url":"https://www.academia.edu/Documents/in/Computational_Economics?f_ri=725","nofollow":true}</script><a class="InlineList-item-text" data-has-card-for-ri="12225" rel="nofollow" href="https://www.academia.edu/Documents/in/GPU_Computing">GPU Computing</a>, <script data-card-contents-for-ri="12225" type="text/json">{"id":12225,"name":"GPU Computing","url":"https://www.academia.edu/Documents/in/GPU_Computing?f_ri=725","nofollow":true}</script><a class="InlineList-item-text" data-has-card-for-ri="16117" rel="nofollow" href="https://www.academia.edu/Documents/in/Agent-Based_Computational_Economics">Agent-Based Computational Economics</a>, <script data-card-contents-for-ri="16117" type="text/json">{"id":16117,"name":"Agent-Based Computational Economics","url":"https://www.academia.edu/Documents/in/Agent-Based_Computational_Economics?f_ri=725","nofollow":true}</script><a class="InlineList-item-text" data-has-card-for-ri="21081" rel="nofollow" href="https://www.academia.edu/Documents/in/GPGPU_General_Purpose_GPU_Programming">GPGPU (General Purpose GPU) Programming</a><script data-card-contents-for-ri="21081" type="text/json">{"id":21081,"name":"GPGPU (General Purpose GPU) Programming","url":"https://www.academia.edu/Documents/in/GPGPU_General_Purpose_GPU_Programming?f_ri=725","nofollow":true}</script></span></li><script>(function(){ if (true) { new Aedu.ResearchInterestListCard({ el: $('*[data-has-card-for-ri-list=19604905]'), work: {"id":19604905,"title":"Accelerating economics: how GPUs can save you time and money","created_at":"2015-12-11T00:28:21.754-08:00","url":"https://www.academia.edu/19604905/Accelerating_economics_how_GPUs_can_save_you_time_and_money?f_ri=725","dom_id":"work_19604905","summary":"Graphics processing units - or GPUs as they are more commonly known - are specialized circuits historically designed to efficiently handle computer graphics. They are highly parallel computers which can process large amounts of data simultaneously. The graphics algorithms for which GPUs have been designed and optimized share characteristics with other algorithms used in high-performance computing. For certain well-suited scientific applications, the GPU's infrastructure has been shown to achieve substantial speedups. For example, the evaluation of the Black-Scholes partial differential equation to price financial options has been found to be performed nearly 200 times faster in parallel on a GPU than serially on a single-core CPU (Buck 2006, “GeForce 8800 \u0026 NVIDIA CUDA: A New Architecture for Computing on the GPU”).\n\nThe main goal of this study is to illustrate how hybrid CPU/GPU systems can be used within computational economics to decrease the execution time of an implementation of a particular model. We start with a mainstream implementation of Raberto et al.'s (2001) Genoa Articial Stock Market (\"GASM\"), an agent-based model which simulates a financial market in discrete time in which heterogeneous agents trade a single asset. In order to ensure that it is well-suited for execution on the GPU, the algorithm used to clear the market according to the authors' specified mechanism is given a particular attention. Existing parallel programming interfaces - in particular the OpenACC standard and Thrust parallel algorithms library - are then deployed in the code. We aim to show:\n\n- how the codebase of our GASM implementation is adapted to utilize these technologies;\n- how incrementally offloading work to the GPU affects the execution time of our model; \n- how this speedup varies as a function of the problem size (e.g. number of agents, number of time steps, etc.), i.e. weak scaling; and\n- how parameterizing the work distribution within the OpenACC programming model to increase the number of execution units used impacts this speedup, i.e. strong scaling.\n\nThis study also aims at giving the reader a working knowledge of GPU-based parallel computing, and when and how it should be used.","downloadable_attachments":[{"id":40726514,"asset_id":19604905,"asset_type":"Work","always_allow_download":false}],"ordered_authors":[{"id":3947075,"first_name":"Laurent","last_name":"Oberholzer","domain_name":"ethz","page_name":"LaurentOberholzer","display_name":"Laurent Oberholzer","profile_url":"https://ethz.academia.edu/LaurentOberholzer?f_ri=725","photo":"/images/s65_no_pic.png"}],"research_interests":[{"id":725,"name":"Computational Economics","url":"https://www.academia.edu/Documents/in/Computational_Economics?f_ri=725","nofollow":true},{"id":12225,"name":"GPU Computing","url":"https://www.academia.edu/Documents/in/GPU_Computing?f_ri=725","nofollow":true},{"id":16117,"name":"Agent-Based Computational Economics","url":"https://www.academia.edu/Documents/in/Agent-Based_Computational_Economics?f_ri=725","nofollow":true},{"id":21081,"name":"GPGPU (General Purpose GPU) Programming","url":"https://www.academia.edu/Documents/in/GPGPU_General_Purpose_GPU_Programming?f_ri=725","nofollow":true},{"id":26704,"name":"Agent-based modeling","url":"https://www.academia.edu/Documents/in/Agent-based_modeling?f_ri=725"},{"id":34050,"name":"Compute Unified Device Architecture NVIDIA CUDA","url":"https://www.academia.edu/Documents/in/Compute_Unified_Device_Architecture_NVIDIA_CUDA?f_ri=725"}]}, }) } })();</script></ul></li></ul></div></div><div class="u-borderBottom1 u-borderColorGrayLighter"><div class="clearfix u-pv7x u-mb0x js-work-card work_1515669" data-work_id="1515669" itemscope="itemscope" itemtype="https://schema.org/ScholarlyArticle"><div class="header"><div class="title u-fontSerif u-fs22 u-lineHeight1_3"><a class="u-tcGrayDarkest js-work-link" href="https://www.academia.edu/1515669/A_COMPARATIVE_STUDY_OF_DOLLAR_COST_AVERAGING_VS_VALUE_AVERAGING">A COMPARATIVE STUDY OF DOLLAR COST AVERAGING VS. VALUE AVERAGING</a></div></div><div class="u-pb4x u-mt3x"><div class="summary u-fs14 u-fw300 u-lineHeight1_5 u-tcGrayDarkest"><div class="summarized">"A COMPARATIVE STUDY OF DOLLAR COST AVERAGING VS. VALUE AVERAGING Pawel S. Benedykcinski and Prof. Rick Goedde (Advisor) Economics Department St. Olaf College Northfield, MN My research compares three investment techniques, fixed... <a class="more_link u-tcGrayDark u-linkUnstyled" data-container=".work_1515669" data-show=".complete" data-hide=".summarized" data-more-link-behavior="true" href="#">more</a></div><div class="complete hidden">"A COMPARATIVE STUDY OF DOLLAR COST AVERAGING VS. VALUE AVERAGING <br />Pawel S. Benedykcinski and Prof. Rick Goedde (Advisor) <br />Economics Department <br />St. Olaf College <br />Northfield, MN <br /> <br />My research compares three investment techniques, fixed and variable dollar cost averaging and value averaging to determine if any of the methods yield superior investment returns in the long run. Mutual funds, stocks, and exchange-traded funds were used to test the methods. Value averaging is a formula-based investment technique using a mathematical formula to guide the investment of money into a portfolio over time. With this method investors contribute to their portfolios in such a way that the portfolio balance increases by a set amount, regardless of market fluctuations. Dollar cost averaging invests equal amounts regularly and periodically over specific time periods in a particular investment or portfolio. By doing so more shares are purchased when prices are low, and fewer shares are purchased when prices are high. <br /> <br />After testing many mutual funds, ETFs, and individual stocks, I concluded that Value Averaging yields better Internal Rates of Return than fixed and variable Dollar Cost Averaging. The results also indicate that the three methods provide superior investment returns over extended investment time periods with little increase in risk, even if prices are volatile. One important difference between these three formula investment techniques is that value averaging requires larger sums of money to be invested at regular time intervals than fixed or variable dollar cost averaging do."</div></div></div><ul class="InlineList u-ph0x u-fs13"><li class="InlineList-item logged_in_only"><div class="share_on_academia_work_button"><a class="academia_share Button Button--inverseBlue Button--sm js-bookmark-button" data-academia-share="Work/1515669" data-share-source="work_strip" data-spinner="small_white_hide_contents"><i class="fa fa-plus"></i><span class="work-strip-link-text u-ml1x" data-content="button_text">Bookmark</span></a></div></li><li class="InlineList-item"><div class="download"><a id="188bf24688c756475934d2d1f770d758" rel="nofollow" data-download="{"attachment_id":12216040,"asset_id":1515669,"asset_type":"Work","always_allow_download":false,"track":null,"button_location":"work_strip","source":null,"hide_modal":null}" class="Button Button--sm Button--inverseGreen js-download-button prompt_button doc_download" href="https://www.academia.edu/attachments/12216040/download_file?st=MTc0MDU1NDU5OCw4LjIyMi4yMDguMTQ2&s=work_strip"><i class="fa fa-arrow-circle-o-down fa-lg"></i><span class="u-textUppercase u-ml1x" data-content="button_text">Download</span></a></div></li><li class="InlineList-item"><ul class="InlineList InlineList--bordered u-ph0x"><li class="InlineList-item InlineList-item--bordered"><span class="InlineList-item-text">by <span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a class="u-tcGrayDark u-fw700" data-has-card-for-user="487090" href="https://stolaf.academia.edu/PawelStefanBenedykcinski">Pawel Stefan Benedykcinski</a><script data-card-contents-for-user="487090" type="text/json">{"id":487090,"first_name":"Pawel Stefan","last_name":"Benedykcinski","domain_name":"stolaf","page_name":"PawelStefanBenedykcinski","display_name":"Pawel Stefan Benedykcinski","profile_url":"https://stolaf.academia.edu/PawelStefanBenedykcinski?f_ri=725","photo":"https://0.academia-photos.com/487090/544014/165435349/s65_pawel_stefan.benedykcinski.jpg"}</script></span></span></li><li class="js-paper-rank-work_1515669 InlineList-item InlineList-item--bordered hidden"><span class="js-paper-rank-view hidden u-tcGrayDark" data-paper-rank-work-id="1515669"><i class="u-m1x fa fa-bar-chart"></i><strong class="js-paper-rank"></strong></span><script>$(function() { new Works.PaperRankView({ workId: 1515669, container: ".js-paper-rank-work_1515669", }); 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$(".js-view-count[data-work-id=1515669]").text(description); $(".js-view-count-work_1515669").attr('title', description).tooltip(); }); });</script></span><script>$(function() { $(".js-view-count-work_1515669").removeClass('hidden') })</script></div></li><li class="InlineList-item u-positionRelative" style="max-width: 250px"><div class="u-positionAbsolute" data-has-card-for-ri-list="1515669"><i class="fa fa-tag InlineList-item-icon u-positionRelative"></i>  <a class="InlineList-item-text u-positionRelative">46</a>  </div><span class="InlineList-item-text u-textTruncate u-pl10x"><a class="InlineList-item-text" data-has-card-for-ri="26" rel="nofollow" href="https://www.academia.edu/Documents/in/Business">Business</a>, <script data-card-contents-for-ri="26" type="text/json">{"id":26,"name":"Business","url":"https://www.academia.edu/Documents/in/Business?f_ri=725","nofollow":true}</script><a class="InlineList-item-text" data-has-card-for-ri="38" rel="nofollow" href="https://www.academia.edu/Documents/in/Management">Management</a>, <script data-card-contents-for-ri="38" type="text/json">{"id":38,"name":"Management","url":"https://www.academia.edu/Documents/in/Management?f_ri=725","nofollow":true}</script><a class="InlineList-item-text" data-has-card-for-ri="47" rel="nofollow" href="https://www.academia.edu/Documents/in/Finance">Finance</a>, <script data-card-contents-for-ri="47" type="text/json">{"id":47,"name":"Finance","url":"https://www.academia.edu/Documents/in/Finance?f_ri=725","nofollow":true}</script><a class="InlineList-item-text" data-has-card-for-ri="305" rel="nofollow" href="https://www.academia.edu/Documents/in/Applied_Mathematics">Applied Mathematics</a><script data-card-contents-for-ri="305" type="text/json">{"id":305,"name":"Applied Mathematics","url":"https://www.academia.edu/Documents/in/Applied_Mathematics?f_ri=725","nofollow":true}</script></span></li><script>(function(){ if (true) { new Aedu.ResearchInterestListCard({ el: $('*[data-has-card-for-ri-list=1515669]'), work: {"id":1515669,"title":"A COMPARATIVE STUDY OF DOLLAR COST AVERAGING VS. VALUE AVERAGING","created_at":"2012-04-19T08:29:32.542-07:00","url":"https://www.academia.edu/1515669/A_COMPARATIVE_STUDY_OF_DOLLAR_COST_AVERAGING_VS_VALUE_AVERAGING?f_ri=725","dom_id":"work_1515669","summary":"\"A COMPARATIVE STUDY OF DOLLAR COST AVERAGING VS. VALUE AVERAGING \r\nPawel S. Benedykcinski and Prof. Rick Goedde (Advisor)\r\nEconomics Department\r\nSt. Olaf College\r\nNorthfield, MN\r\n\r\nMy research compares three investment techniques, fixed and variable dollar cost averaging and value averaging to determine if any of the methods yield superior investment returns in the long run. Mutual funds, stocks, and exchange-traded funds were used to test the methods. Value averaging is a formula-based investment technique using a mathematical formula to guide the investment of money into a portfolio over time. With this method investors contribute to their portfolios in such a way that the portfolio balance increases by a set amount, regardless of market fluctuations. Dollar cost averaging invests equal amounts regularly and periodically over specific time periods in a particular investment or portfolio. By doing so more shares are purchased when prices are low, and fewer shares are purchased when prices are high.\r\n\r\nAfter testing many mutual funds, ETFs, and individual stocks, I concluded that Value Averaging yields better Internal Rates of Return than fixed and variable Dollar Cost Averaging. The results also indicate that the three methods provide superior investment returns over extended investment time periods with little increase in risk, even if prices are volatile. One important difference between these three formula investment techniques is that value averaging requires larger sums of money to be invested at regular time intervals than fixed or variable dollar cost averaging do.\"","downloadable_attachments":[{"id":12216040,"asset_id":1515669,"asset_type":"Work","always_allow_download":false}],"ordered_authors":[{"id":487090,"first_name":"Pawel Stefan","last_name":"Benedykcinski","domain_name":"stolaf","page_name":"PawelStefanBenedykcinski","display_name":"Pawel Stefan Benedykcinski","profile_url":"https://stolaf.academia.edu/PawelStefanBenedykcinski?f_ri=725","photo":"https://0.academia-photos.com/487090/544014/165435349/s65_pawel_stefan.benedykcinski.jpg"}],"research_interests":[{"id":26,"name":"Business","url":"https://www.academia.edu/Documents/in/Business?f_ri=725","nofollow":true},{"id":38,"name":"Management","url":"https://www.academia.edu/Documents/in/Management?f_ri=725","nofollow":true},{"id":47,"name":"Finance","url":"https://www.academia.edu/Documents/in/Finance?f_ri=725","nofollow":true},{"id":305,"name":"Applied Mathematics","url":"https://www.academia.edu/Documents/in/Applied_Mathematics?f_ri=725","nofollow":true},{"id":724,"name":"Economics","url":"https://www.academia.edu/Documents/in/Economics?f_ri=725"},{"id":725,"name":"Computational Economics","url":"https://www.academia.edu/Documents/in/Computational_Economics?f_ri=725"},{"id":748,"name":"Financial 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Markets","url":"https://www.academia.edu/Documents/in/Fixed_Income_Markets?f_ri=725"}]}, }) } })();</script></ul></li></ul></div></div><div class="u-borderBottom1 u-borderColorGrayLighter"><div class="clearfix u-pv7x u-mb0x js-work-card work_21925498" data-work_id="21925498" itemscope="itemscope" itemtype="https://schema.org/ScholarlyArticle"><div class="header"><div class="title u-fontSerif u-fs22 u-lineHeight1_3"><a class="u-tcGrayDarkest js-work-link" href="https://www.academia.edu/21925498/Display_and_Interactive_Languages_for_the_Internet_HTML_PDF_and_Java">Display and Interactive Languages for the Internet: HTML, PDF, and Java</a></div></div><div class="u-pb4x u-mt3x"><div class="summary u-fs14 u-fw300 u-lineHeight1_5 u-tcGrayDarkest"><div class="summarized">The rapid rise of the Internet has lead to new technologies. These include HTML, the basic 'markup' language for pages on the World Wide Web; PDF, a file format designed for precise layout control of documents like working papers and... <a class="more_link u-tcGrayDark u-linkUnstyled" data-container=".work_21925498" data-show=".complete" data-hide=".summarized" data-more-link-behavior="true" href="#">more</a></div><div class="complete hidden">The rapid rise of the Internet has lead to new technologies. These include HTML, the basic 'markup' language for pages on the World Wide Web; PDF, a file format designed for precise layout control of documents like working papers and journals, and Java, a general purpose language ideally suited for use on the Internet. This paper introduces these technologies.</div></div></div><ul class="InlineList u-ph0x u-fs13"><li class="InlineList-item logged_in_only"><div class="share_on_academia_work_button"><a class="academia_share Button Button--inverseBlue Button--sm js-bookmark-button" data-academia-share="Work/21925498" data-share-source="work_strip" data-spinner="small_white_hide_contents"><i class="fa fa-plus"></i><span class="work-strip-link-text u-ml1x" data-content="button_text">Bookmark</span></a></div></li><li class="InlineList-item"><div class="download"><a id="e0093f0192f0356f939b25703964bf86" rel="nofollow" data-download="{"attachment_id":42653218,"asset_id":21925498,"asset_type":"Work","always_allow_download":false,"track":null,"button_location":"work_strip","source":null,"hide_modal":null}" class="Button Button--sm Button--inverseGreen js-download-button prompt_button doc_download" href="https://www.academia.edu/attachments/42653218/download_file?st=MTc0MDU1NDU5OSw4LjIyMi4yMDguMTQ2&s=work_strip"><i class="fa fa-arrow-circle-o-down fa-lg"></i><span class="u-textUppercase u-ml1x" data-content="button_text">Download</span></a></div></li><li class="InlineList-item"><ul class="InlineList InlineList--bordered u-ph0x"><li class="InlineList-item InlineList-item--bordered"><span class="InlineList-item-text">by <span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a class="u-tcGrayDark u-fw700" data-has-card-for-user="42734970" href="https://independent.academia.edu/DirkEddelbuettel">Dirk Eddelbuettel</a><script data-card-contents-for-user="42734970" type="text/json">{"id":42734970,"first_name":"Dirk","last_name":"Eddelbuettel","domain_name":"independent","page_name":"DirkEddelbuettel","display_name":"Dirk Eddelbuettel","profile_url":"https://independent.academia.edu/DirkEddelbuettel?f_ri=725","photo":"https://gravatar.com/avatar/4e96ca7ae02c37e7d940d17997d780e5?s=65"}</script></span></span></li><li class="js-paper-rank-work_21925498 InlineList-item InlineList-item--bordered hidden"><span class="js-paper-rank-view hidden u-tcGrayDark" data-paper-rank-work-id="21925498"><i class="u-m1x fa fa-bar-chart"></i><strong class="js-paper-rank"></strong></span><script>$(function() { new Works.PaperRankView({ workId: 21925498, container: ".js-paper-rank-work_21925498", }); 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This paper introduces these technologies.","downloadable_attachments":[{"id":42653218,"asset_id":21925498,"asset_type":"Work","always_allow_download":false}],"ordered_authors":[{"id":42734970,"first_name":"Dirk","last_name":"Eddelbuettel","domain_name":"independent","page_name":"DirkEddelbuettel","display_name":"Dirk Eddelbuettel","profile_url":"https://independent.academia.edu/DirkEddelbuettel?f_ri=725","photo":"https://gravatar.com/avatar/4e96ca7ae02c37e7d940d17997d780e5?s=65"}],"research_interests":[{"id":725,"name":"Computational Economics","url":"https://www.academia.edu/Documents/in/Computational_Economics?f_ri=725","nofollow":true},{"id":747,"name":"Econometrics","url":"https://www.academia.edu/Documents/in/Econometrics?f_ri=725","nofollow":true}]}, }) } })();</script></ul></li></ul></div></div><div class="u-borderBottom1 u-borderColorGrayLighter"><div class="clearfix u-pv7x u-mb0x js-work-card work_70838866" data-work_id="70838866" itemscope="itemscope" itemtype="https://schema.org/ScholarlyArticle"><div class="header"><div class="title u-fontSerif u-fs22 u-lineHeight1_3"><a class="u-tcGrayDarkest js-work-link" rel="nofollow" href="https://www.academia.edu/70838866/Economic_Evaluation_of_CO2_Sequestration_Technologies_Task_4_Biomass_Gasification_Based_Processing">Economic Evaluation of CO2 Sequestration Technologies Task 4, Biomass Gasification-Based Processing</a></div></div><div class="u-pb4x u-mt3x"><div class="summary u-fs14 u-fw300 u-lineHeight1_5 u-tcGrayDarkest"><div class="summarized">DOE Scientific and Technical ... Publication Date, 2002 Jun 01. OSTI Identifier, OSTI ID: 802155. Report Number(s), FC26-00NT40937--03. DOE Contract Number, FC26-00NT40937. DOI, 10.2172/802155. Other Number(s), TRN: US200223%%920.... <a class="more_link u-tcGrayDark u-linkUnstyled" data-container=".work_70838866" data-show=".complete" data-hide=".summarized" data-more-link-behavior="true" href="#">more</a></div><div class="complete hidden">DOE Scientific and Technical ... Publication Date, 2002 Jun 01. OSTI Identifier, OSTI ID: 802155. Report Number(s), FC26-00NT40937--03. DOE Contract Number, FC26-00NT40937. DOI, 10.2172/802155. Other Number(s), TRN: US200223%%920. Resource Type, Technical Report ...</div></div></div><ul class="InlineList u-ph0x u-fs13"><li class="InlineList-item logged_in_only"><div class="share_on_academia_work_button"><a class="academia_share Button Button--inverseBlue Button--sm js-bookmark-button" data-academia-share="Work/70838866" data-share-source="work_strip" data-spinner="small_white_hide_contents"><i class="fa fa-plus"></i><span class="work-strip-link-text u-ml1x" data-content="button_text">Bookmark</span></a></div></li><li class="InlineList-item"><div class="download"><a id="406639d0599f0d19a4454a6a179e675a" rel="nofollow" data-download="{"attachment_id":80418682,"asset_id":70838866,"asset_type":"Work","always_allow_download":false,"track":null,"button_location":"work_strip","source":null,"hide_modal":null}" class="Button Button--sm Button--inverseGreen js-download-button prompt_button doc_download" href="https://www.academia.edu/attachments/80418682/download_file?st=MTc0MDU1NDU5OSw4LjIyMi4yMDguMTQ2&s=work_strip"><i class="fa fa-arrow-circle-o-down fa-lg"></i><span class="u-textUppercase u-ml1x" data-content="button_text">Download</span></a></div></li><li class="InlineList-item"><ul class="InlineList InlineList--bordered u-ph0x"><li class="InlineList-item InlineList-item--bordered"><span class="InlineList-item-text">by <span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a class="u-tcGrayDark u-fw700" data-has-card-for-user="2652229" href="https://independent.academia.edu/BertBock">Bert Bock</a><script data-card-contents-for-user="2652229" type="text/json">{"id":2652229,"first_name":"Bert","last_name":"Bock","domain_name":"independent","page_name":"BertBock","display_name":"Bert Bock","profile_url":"https://independent.academia.edu/BertBock?f_ri=725","photo":"https://0.academia-photos.com/2652229/846326/1051971/s65_bert.bock.jpg"}</script></span></span></li><li class="js-paper-rank-work_70838866 InlineList-item InlineList-item--bordered hidden"><span class="js-paper-rank-view hidden u-tcGrayDark" data-paper-rank-work-id="70838866"><i class="u-m1x fa fa-bar-chart"></i><strong class="js-paper-rank"></strong></span><script>$(function() { new Works.PaperRankView({ workId: 70838866, container: ".js-paper-rank-work_70838866", }); 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Publication Date, 2002 Jun 01. OSTI Identifier, OSTI ID: 802155. Report Number(s), FC26-00NT40937--03. DOE Contract Number, FC26-00NT40937. DOI, 10.2172/802155. Other Number(s), TRN: US200223%%920. 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If neither wage and price adjustment nor monetary policy are effective at stimulating demand, no endogenous dynamic process exists to assure that demand grows... <a class="more_link u-tcGrayDark u-linkUnstyled" data-container=".work_11353307" data-show=".complete" data-hide=".summarized" data-more-link-behavior="true" href="#">more</a></div><div class="complete hidden">This paper considers a puzzle in growth theory from a Keynesian perspective. If neither wage and price adjustment nor monetary policy are effective at stimulating demand, no endogenous dynamic process exists to assure that demand grows fast enough to employ a growing labor force. Yet output grows persistently over long periods, occasionally reaching approximate full employment. We resolve this puzzle by invoking Harrod's instability results. Demand grows because it follows an explosive upward path that is ultimately limited by resource constraints. Downward demand instability is contained by introducing an autonomous component to aggregate demand.</div></div></div><ul class="InlineList u-ph0x u-fs13"><li class="InlineList-item logged_in_only"><div class="share_on_academia_work_button"><a class="academia_share Button Button--inverseBlue Button--sm js-bookmark-button" data-academia-share="Work/11353307" data-share-source="work_strip" data-spinner="small_white_hide_contents"><i class="fa fa-plus"></i><span class="work-strip-link-text u-ml1x" data-content="button_text">Bookmark</span></a></div></li><li class="InlineList-item"><div class="download"><a id="a86f9c6a9b2f3804a485790167924cf3" rel="nofollow" data-download="{"attachment_id":46751931,"asset_id":11353307,"asset_type":"Work","always_allow_download":false,"track":null,"button_location":"work_strip","source":null,"hide_modal":null}" class="Button Button--sm Button--inverseGreen js-download-button prompt_button doc_download" href="https://www.academia.edu/attachments/46751931/download_file?st=MTc0MDU1NDU5OSw4LjIyMi4yMDguMTQ2&s=work_strip"><i class="fa fa-arrow-circle-o-down fa-lg"></i><span class="u-textUppercase u-ml1x" data-content="button_text">Download</span></a></div></li><li class="InlineList-item"><ul class="InlineList InlineList--bordered u-ph0x"><li class="InlineList-item InlineList-item--bordered"><span class="InlineList-item-text">by <span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a class="u-tcGrayDark u-fw700" data-has-card-for-user="27575588" href="https://unibg.academia.edu/AnnaMariaVariato">Anna Maria Variato</a><script data-card-contents-for-user="27575588" type="text/json">{"id":27575588,"first_name":"Anna Maria","last_name":"Variato","domain_name":"unibg","page_name":"AnnaMariaVariato","display_name":"Anna Maria Variato","profile_url":"https://unibg.academia.edu/AnnaMariaVariato?f_ri=725","photo":"/images/s65_no_pic.png"}</script></span></span><span class="u-displayInlineBlock InlineList-item-text"> and <span class="u-textDecorationUnderline u-clickable InlineList-item-text js-work-more-authors-11353307">+1</span><div class="hidden js-additional-users-11353307"><div><span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a href="https://independent.academia.edu/PieroFerri">Piero Ferri</a></span></div></div></span><script>(function(){ var popoverSettings = { el: $('.js-work-more-authors-11353307'), placement: 'bottom', hide_delay: 200, html: true, content: function(){ return $('.js-additional-users-11353307').html(); 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container.find('.percentile-widget').removeClass('hidden'); }); });</script></li><li class="js-view-count-work_11353307 InlineList-item InlineList-item--bordered hidden"><div><span><span class="js-view-count view-count u-mr2x" data-work-id="11353307"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 11353307; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=11353307]").text(description); $(".js-view-count-work_11353307").attr('title', description).tooltip(); }); });</script></span><script>$(function() { $(".js-view-count-work_11353307").removeClass('hidden') })</script></div></li><li class="InlineList-item u-positionRelative" style="max-width: 250px"><div class="u-positionAbsolute" data-has-card-for-ri-list="11353307"><i class="fa fa-tag InlineList-item-icon u-positionRelative"></i>  <a class="InlineList-item-text u-positionRelative">4</a>  </div><span class="InlineList-item-text u-textTruncate u-pl9x"><a class="InlineList-item-text" data-has-card-for-ri="725" rel="nofollow" href="https://www.academia.edu/Documents/in/Computational_Economics">Computational Economics</a>, <script data-card-contents-for-ri="725" type="text/json">{"id":725,"name":"Computational Economics","url":"https://www.academia.edu/Documents/in/Computational_Economics?f_ri=725","nofollow":true}</script><a class="InlineList-item-text" data-has-card-for-ri="747" rel="nofollow" href="https://www.academia.edu/Documents/in/Econometrics">Econometrics</a>, <script data-card-contents-for-ri="747" type="text/json">{"id":747,"name":"Econometrics","url":"https://www.academia.edu/Documents/in/Econometrics?f_ri=725","nofollow":true}</script><a class="InlineList-item-text" data-has-card-for-ri="63679" rel="nofollow" href="https://www.academia.edu/Documents/in/Instability">Instability</a>, <script data-card-contents-for-ri="63679" type="text/json">{"id":63679,"name":"Instability","url":"https://www.academia.edu/Documents/in/Instability?f_ri=725","nofollow":true}</script><a class="InlineList-item-text" data-has-card-for-ri="244111" rel="nofollow" href="https://www.academia.edu/Documents/in/Fluctuations">Fluctuations</a><script data-card-contents-for-ri="244111" type="text/json">{"id":244111,"name":"Fluctuations","url":"https://www.academia.edu/Documents/in/Fluctuations?f_ri=725","nofollow":true}</script></span></li><script>(function(){ if (true) { new Aedu.ResearchInterestListCard({ el: $('*[data-has-card-for-ri-list=11353307]'), work: {"id":11353307,"title":"Aggregate Demand, Harrod’s Instability and Fluctuations","created_at":"2015-03-10T07:44:28.635-07:00","url":"https://www.academia.edu/11353307/Aggregate_Demand_Harrod_s_Instability_and_Fluctuations?f_ri=725","dom_id":"work_11353307","summary":"This paper considers a puzzle in growth theory from a Keynesian perspective. If neither wage and price adjustment nor monetary policy are effective at stimulating demand, no endogenous dynamic process exists to assure that demand grows fast enough to employ a growing labor force. Yet output grows persistently over long periods, occasionally reaching approximate full employment. We resolve this puzzle by invoking Harrod's instability results. Demand grows because it follows an explosive upward path that is ultimately limited by resource constraints. Downward demand instability is contained by introducing an autonomous component to aggregate demand.","downloadable_attachments":[{"id":46751931,"asset_id":11353307,"asset_type":"Work","always_allow_download":false}],"ordered_authors":[{"id":27575588,"first_name":"Anna Maria","last_name":"Variato","domain_name":"unibg","page_name":"AnnaMariaVariato","display_name":"Anna Maria Variato","profile_url":"https://unibg.academia.edu/AnnaMariaVariato?f_ri=725","photo":"/images/s65_no_pic.png"},{"id":71941072,"first_name":"Piero","last_name":"Ferri","domain_name":"independent","page_name":"PieroFerri","display_name":"Piero Ferri","profile_url":"https://independent.academia.edu/PieroFerri?f_ri=725","photo":"/images/s65_no_pic.png"}],"research_interests":[{"id":725,"name":"Computational Economics","url":"https://www.academia.edu/Documents/in/Computational_Economics?f_ri=725","nofollow":true},{"id":747,"name":"Econometrics","url":"https://www.academia.edu/Documents/in/Econometrics?f_ri=725","nofollow":true},{"id":63679,"name":"Instability","url":"https://www.academia.edu/Documents/in/Instability?f_ri=725","nofollow":true},{"id":244111,"name":"Fluctuations","url":"https://www.academia.edu/Documents/in/Fluctuations?f_ri=725","nofollow":true}]}, }) } })();</script></ul></li></ul></div></div><div class="u-borderBottom1 u-borderColorGrayLighter"><div class="clearfix u-pv7x u-mb0x js-work-card work_52482087" data-work_id="52482087" itemscope="itemscope" itemtype="https://schema.org/ScholarlyArticle"><div class="header"><div class="title u-fontSerif u-fs22 u-lineHeight1_3"><a class="u-tcGrayDarkest js-work-link" href="https://www.academia.edu/52482087/Computation_in_Economics">Computation in Economics</a></div></div><div class="u-pb4x u-mt3x"><div class="summary u-fs14 u-fw300 u-lineHeight1_5 u-tcGrayDarkest"><div class="summarized">or see <a href="http://www.assru.economia.unitn.it/" rel="nofollow">http://www.assru.economia.unitn.it/</a>. The ASSRU logo depicts a Counting table (woodcut probably from Strasbourg). The spaces between the lines function as the wires on an abacus. The place value is marked at the end. ♥ Forthcoming... <a class="more_link u-tcGrayDark u-linkUnstyled" data-container=".work_52482087" data-show=".complete" data-hide=".summarized" data-more-link-behavior="true" href="#">more</a></div><div class="complete hidden">or see <a href="http://www.assru.economia.unitn.it/" rel="nofollow">http://www.assru.economia.unitn.it/</a>. The ASSRU logo depicts a Counting table (woodcut probably from Strasbourg). The spaces between the lines function as the wires on an abacus. The place value is marked at the end. ♥ Forthcoming in: The Elgar Companion to Recent Economic Methodology, edited by John Davis & Wade Hands, Edward Elgar Publishing, Cheltenham, Glos., & Northampton, MA, (2011). We are greatly indebted to the Editors for the kind invitation to contribute and the immense patience with which they tolerated the various ways in which we transcended generous deadlines. The title has metamorphosed into the ultra-simple final form it has taken, having begun its life as Computational Economics, become the Computational Paradigm in Economics, then Computational Economics, Computable General Equilibrium Theory & Computable Economics and, finally, Classical Behavioural Economics, Computable General Equilibrium Theory, Computable Economics and Agent-Based Computational Economics. Each of the transitional titles seemed, at least to the authors, of emphasizing particular kinds of ways the notion of machine computation, and its underpinning theory, were implemented in a variety of economic theories. To avoid any such connotation it seemed best to choose as neutral a title as possible, without losing focus on the main theme which is, of course, the foundations of the methodology of computing in economics. We are deeply indebted to our two graduate students, Selda Kao and V. Ragupathy, for invaluable logistical and intellectual help. Alas, they refuse to take any blame for the remaining infelicities.</div></div></div><ul class="InlineList u-ph0x u-fs13"><li class="InlineList-item logged_in_only"><div class="share_on_academia_work_button"><a class="academia_share Button Button--inverseBlue Button--sm js-bookmark-button" data-academia-share="Work/52482087" data-share-source="work_strip" data-spinner="small_white_hide_contents"><i class="fa fa-plus"></i><span class="work-strip-link-text u-ml1x" data-content="button_text">Bookmark</span></a></div></li><li class="InlineList-item"><div class="download"><a id="18b69dff5d1f9a0347e5693126577434" rel="nofollow" data-download="{"attachment_id":69728133,"asset_id":52482087,"asset_type":"Work","always_allow_download":false,"track":null,"button_location":"work_strip","source":null,"hide_modal":null}" class="Button Button--sm Button--inverseGreen js-download-button prompt_button doc_download" href="https://www.academia.edu/attachments/69728133/download_file?st=MTc0MDU1NDU5OSw4LjIyMi4yMDguMTQ2&s=work_strip"><i class="fa fa-arrow-circle-o-down fa-lg"></i><span class="u-textUppercase u-ml1x" data-content="button_text">Download</span></a></div></li><li class="InlineList-item"><ul class="InlineList InlineList--bordered u-ph0x"><li class="InlineList-item InlineList-item--bordered"><span class="InlineList-item-text">by <span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a class="u-tcGrayDark u-fw700" data-has-card-for-user="190616897" href="https://independent.academia.edu/StefanoZambelli3">Stefano Zambelli</a><script data-card-contents-for-user="190616897" type="text/json">{"id":190616897,"first_name":"Stefano","last_name":"Zambelli","domain_name":"independent","page_name":"StefanoZambelli3","display_name":"Stefano Zambelli","profile_url":"https://independent.academia.edu/StefanoZambelli3?f_ri=725","photo":"https://0.academia-photos.com/190616897/53854190/41988031/s65_stefano.zambelli.png"}</script></span></span></li><li class="js-paper-rank-work_52482087 InlineList-item InlineList-item--bordered hidden"><span class="js-paper-rank-view hidden u-tcGrayDark" data-paper-rank-work-id="52482087"><i class="u-m1x fa fa-bar-chart"></i><strong class="js-paper-rank"></strong></span><script>$(function() { new Works.PaperRankView({ workId: 52482087, container: ".js-paper-rank-work_52482087", }); 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$(".js-view-count[data-work-id=52482087]").text(description); $(".js-view-count-work_52482087").attr('title', description).tooltip(); }); });</script></span><script>$(function() { $(".js-view-count-work_52482087").removeClass('hidden') })</script></div></li><li class="InlineList-item u-positionRelative" style="max-width: 250px"><div class="u-positionAbsolute" data-has-card-for-ri-list="52482087"><i class="fa fa-tag InlineList-item-icon u-positionRelative"></i>  <a class="InlineList-item-text u-positionRelative">7</a>  </div><span class="InlineList-item-text u-textTruncate u-pl9x"><a class="InlineList-item-text" data-has-card-for-ri="725" rel="nofollow" href="https://www.academia.edu/Documents/in/Computational_Economics">Computational Economics</a>, <script data-card-contents-for-ri="725" type="text/json">{"id":725,"name":"Computational Economics","url":"https://www.academia.edu/Documents/in/Computational_Economics?f_ri=725","nofollow":true}</script><a class="InlineList-item-text" data-has-card-for-ri="6208" rel="nofollow" href="https://www.academia.edu/Documents/in/Economic_Theory">Economic Theory</a>, <script data-card-contents-for-ri="6208" type="text/json">{"id":6208,"name":"Economic Theory","url":"https://www.academia.edu/Documents/in/Economic_Theory?f_ri=725","nofollow":true}</script><a class="InlineList-item-text" data-has-card-for-ri="7406" rel="nofollow" href="https://www.academia.edu/Documents/in/Agent_Based">Agent Based</a>, <script data-card-contents-for-ri="7406" type="text/json">{"id":7406,"name":"Agent Based","url":"https://www.academia.edu/Documents/in/Agent_Based?f_ri=725","nofollow":true}</script><a class="InlineList-item-text" data-has-card-for-ri="12022" rel="nofollow" href="https://www.academia.edu/Documents/in/Numerical_Analysis">Numerical Analysis</a><script data-card-contents-for-ri="12022" type="text/json">{"id":12022,"name":"Numerical Analysis","url":"https://www.academia.edu/Documents/in/Numerical_Analysis?f_ri=725","nofollow":true}</script></span></li><script>(function(){ if (true) { new Aedu.ResearchInterestListCard({ el: $('*[data-has-card-for-ri-list=52482087]'), work: {"id":52482087,"title":"Computation in Economics","created_at":"2021-09-15T22:44:52.805-07:00","url":"https://www.academia.edu/52482087/Computation_in_Economics?f_ri=725","dom_id":"work_52482087","summary":"or see http://www.assru.economia.unitn.it/. The ASSRU logo depicts a Counting table (woodcut probably from Strasbourg). The spaces between the lines function as the wires on an abacus. The place value is marked at the end. ♥ Forthcoming in: The Elgar Companion to Recent Economic Methodology, edited by John Davis \u0026 Wade Hands, Edward Elgar Publishing, Cheltenham, Glos., \u0026 Northampton, MA, (2011). We are greatly indebted to the Editors for the kind invitation to contribute and the immense patience with which they tolerated the various ways in which we transcended generous deadlines. The title has metamorphosed into the ultra-simple final form it has taken, having begun its life as Computational Economics, become the Computational Paradigm in Economics, then Computational Economics, Computable General Equilibrium Theory \u0026 Computable Economics and, finally, Classical Behavioural Economics, Computable General Equilibrium Theory, Computable Economics and Agent-Based Computational Economics. Each of the transitional titles seemed, at least to the authors, of emphasizing particular kinds of ways the notion of machine computation, and its underpinning theory, were implemented in a variety of economic theories. To avoid any such connotation it seemed best to choose as neutral a title as possible, without losing focus on the main theme which is, of course, the foundations of the methodology of computing in economics. We are deeply indebted to our two graduate students, Selda Kao and V. Ragupathy, for invaluable logistical and intellectual help. Alas, they refuse to take any blame for the remaining infelicities.","downloadable_attachments":[{"id":69728133,"asset_id":52482087,"asset_type":"Work","always_allow_download":false}],"ordered_authors":[{"id":190616897,"first_name":"Stefano","last_name":"Zambelli","domain_name":"independent","page_name":"StefanoZambelli3","display_name":"Stefano Zambelli","profile_url":"https://independent.academia.edu/StefanoZambelli3?f_ri=725","photo":"https://0.academia-photos.com/190616897/53854190/41988031/s65_stefano.zambelli.png"}],"research_interests":[{"id":725,"name":"Computational Economics","url":"https://www.academia.edu/Documents/in/Computational_Economics?f_ri=725","nofollow":true},{"id":6208,"name":"Economic Theory","url":"https://www.academia.edu/Documents/in/Economic_Theory?f_ri=725","nofollow":true},{"id":7406,"name":"Agent Based","url":"https://www.academia.edu/Documents/in/Agent_Based?f_ri=725","nofollow":true},{"id":12022,"name":"Numerical Analysis","url":"https://www.academia.edu/Documents/in/Numerical_Analysis?f_ri=725","nofollow":true},{"id":79158,"name":"Computable General Equilibrium","url":"https://www.academia.edu/Documents/in/Computable_General_Equilibrium?f_ri=725"},{"id":925792,"name":"Computability","url":"https://www.academia.edu/Documents/in/Computability?f_ri=725"},{"id":1226770,"name":"Behavioural Economics","url":"https://www.academia.edu/Documents/in/Behavioural_Economics?f_ri=725"}]}, }) } })();</script></ul></li></ul></div></div><div class="u-borderBottom1 u-borderColorGrayLighter"><div class="clearfix u-pv7x u-mb0x js-work-card work_68285011" data-work_id="68285011" itemscope="itemscope" itemtype="https://schema.org/ScholarlyArticle"><div class="header"><div class="title u-fontSerif u-fs22 u-lineHeight1_3"><a class="u-tcGrayDarkest js-work-link" href="https://www.academia.edu/68285011/Matlab_Python_Julia_What_to_Choose_in_Economics">Matlab, Python, Julia: What to Choose in Economics?</a></div></div><div class="u-pb4x u-mt3x"><div class="summary u-fs14 u-fw300 u-lineHeight1_5 u-tcGrayDarkest"><div class="summarized">We perform a comparison of Matlab, Python and Julia as programming languages to be used for implementing global nonlinear solution techniques. We consider two popular applications: a neoclassical growth model and a new Keynesian model.... <a class="more_link u-tcGrayDark u-linkUnstyled" data-container=".work_68285011" data-show=".complete" data-hide=".summarized" data-more-link-behavior="true" href="#">more</a></div><div class="complete hidden">We perform a comparison of Matlab, Python and Julia as programming languages to be used for implementing global nonlinear solution techniques. We consider two popular applications: a neoclassical growth model and a new Keynesian model. The goal of our analysis is twofold: First, it is aimed at helping researchers in economics choose the programming language that is best suited to their applications and, if needed, help them transit from one programming language to another. Second, our collections of routines can be viewed as a toolbox with a special emphasis on techniques for dealing with high dimensional economic problems. We provide the routines in the three languages for constructing random and quasi-random grids, low-cost monomial integration, various global solution methods, routines for checking the accuracy of the solutions as well as examples of parallelization. Our global solution methods are not only accurate but also fast. Solving a new Keynesian model with eight state variables only takes a few seconds, even in the presence of an active zero lower bound on nominal interest rates. This speed is important because it allows the model to be solved repeatedly as would be required for estimation.</div></div></div><ul class="InlineList u-ph0x u-fs13"><li class="InlineList-item logged_in_only"><div class="share_on_academia_work_button"><a class="academia_share Button Button--inverseBlue Button--sm js-bookmark-button" data-academia-share="Work/68285011" data-share-source="work_strip" data-spinner="small_white_hide_contents"><i class="fa fa-plus"></i><span class="work-strip-link-text u-ml1x" data-content="button_text">Bookmark</span></a></div></li><li class="InlineList-item"><div class="download"><a id="c677a2174c529a8a9f42df0e1d7ec95a" rel="nofollow" data-download="{"attachment_id":78815211,"asset_id":68285011,"asset_type":"Work","always_allow_download":false,"track":null,"button_location":"work_strip","source":null,"hide_modal":null}" class="Button Button--sm Button--inverseGreen js-download-button prompt_button doc_download" href="https://www.academia.edu/attachments/78815211/download_file?st=MTc0MDU1NDU5OSw4LjIyMi4yMDguMTQ2&s=work_strip"><i class="fa fa-arrow-circle-o-down fa-lg"></i><span class="u-textUppercase u-ml1x" data-content="button_text">Download</span></a></div></li><li class="InlineList-item"><ul class="InlineList InlineList--bordered u-ph0x"><li class="InlineList-item InlineList-item--bordered"><span class="InlineList-item-text">by <span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a class="u-tcGrayDark u-fw700" data-has-card-for-user="98666670" href="https://gc-cuny.academia.edu/liliamaliar">lilia maliar</a><script data-card-contents-for-user="98666670" type="text/json">{"id":98666670,"first_name":"lilia","last_name":"maliar","domain_name":"gc-cuny","page_name":"liliamaliar","display_name":"lilia maliar","profile_url":"https://gc-cuny.academia.edu/liliamaliar?f_ri=725","photo":"https://0.academia-photos.com/98666670/26811480/25287815/s65_lilia.maliar.jpg"}</script></span></span></li><li class="js-paper-rank-work_68285011 InlineList-item InlineList-item--bordered hidden"><span class="js-paper-rank-view hidden u-tcGrayDark" data-paper-rank-work-id="68285011"><i class="u-m1x fa fa-bar-chart"></i><strong class="js-paper-rank"></strong></span><script>$(function() { new Works.PaperRankView({ workId: 68285011, container: ".js-paper-rank-work_68285011", }); });</script></li><li class="js-percentile-work_68285011 InlineList-item InlineList-item--bordered hidden u-tcGrayDark"><span class="percentile-widget hidden"><span class="u-mr2x percentile-widget" style="display: none">•</span><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 68285011; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-percentile-work_68285011"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></li><li class="js-view-count-work_68285011 InlineList-item InlineList-item--bordered hidden"><div><span><span class="js-view-count view-count u-mr2x" data-work-id="68285011"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 68285011; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=68285011]").text(description); $(".js-view-count-work_68285011").attr('title', description).tooltip(); }); });</script></span><script>$(function() { $(".js-view-count-work_68285011").removeClass('hidden') })</script></div></li><li class="InlineList-item u-positionRelative" style="max-width: 250px"><div class="u-positionAbsolute" data-has-card-for-ri-list="68285011"><i class="fa fa-tag InlineList-item-icon u-positionRelative"></i>  <a class="InlineList-item-text u-positionRelative">4</a>  </div><span class="InlineList-item-text u-textTruncate u-pl9x"><a class="InlineList-item-text" data-has-card-for-ri="422" rel="nofollow" href="https://www.academia.edu/Documents/in/Computer_Science">Computer Science</a>, <script data-card-contents-for-ri="422" type="text/json">{"id":422,"name":"Computer Science","url":"https://www.academia.edu/Documents/in/Computer_Science?f_ri=725","nofollow":true}</script><a class="InlineList-item-text" data-has-card-for-ri="725" rel="nofollow" href="https://www.academia.edu/Documents/in/Computational_Economics">Computational Economics</a>, <script data-card-contents-for-ri="725" type="text/json">{"id":725,"name":"Computational Economics","url":"https://www.academia.edu/Documents/in/Computational_Economics?f_ri=725","nofollow":true}</script><a class="InlineList-item-text" data-has-card-for-ri="747" rel="nofollow" href="https://www.academia.edu/Documents/in/Econometrics">Econometrics</a>, <script data-card-contents-for-ri="747" type="text/json">{"id":747,"name":"Econometrics","url":"https://www.academia.edu/Documents/in/Econometrics?f_ri=725","nofollow":true}</script><a class="InlineList-item-text" data-has-card-for-ri="3079415" rel="nofollow" href="https://www.academia.edu/Documents/in/Finance_and_Investment_Banking">Finance and Investment Banking</a><script data-card-contents-for-ri="3079415" type="text/json">{"id":3079415,"name":"Finance and Investment Banking","url":"https://www.academia.edu/Documents/in/Finance_and_Investment_Banking?f_ri=725","nofollow":true}</script></span></li><script>(function(){ if (true) { new Aedu.ResearchInterestListCard({ el: $('*[data-has-card-for-ri-list=68285011]'), work: {"id":68285011,"title":"Matlab, Python, Julia: What to Choose in Economics?","created_at":"2022-01-15T07:14:44.163-08:00","url":"https://www.academia.edu/68285011/Matlab_Python_Julia_What_to_Choose_in_Economics?f_ri=725","dom_id":"work_68285011","summary":"We perform a comparison of Matlab, Python and Julia as programming languages to be used for implementing global nonlinear solution techniques. We consider two popular applications: a neoclassical growth model and a new Keynesian model. The goal of our analysis is twofold: First, it is aimed at helping researchers in economics choose the programming language that is best suited to their applications and, if needed, help them transit from one programming language to another. Second, our collections of routines can be viewed as a toolbox with a special emphasis on techniques for dealing with high dimensional economic problems. We provide the routines in the three languages for constructing random and quasi-random grids, low-cost monomial integration, various global solution methods, routines for checking the accuracy of the solutions as well as examples of parallelization. Our global solution methods are not only accurate but also fast. Solving a new Keynesian model with eight state variables only takes a few seconds, even in the presence of an active zero lower bound on nominal interest rates. This speed is important because it allows the model to be solved repeatedly as would be required for estimation.","downloadable_attachments":[{"id":78815211,"asset_id":68285011,"asset_type":"Work","always_allow_download":false}],"ordered_authors":[{"id":98666670,"first_name":"lilia","last_name":"maliar","domain_name":"gc-cuny","page_name":"liliamaliar","display_name":"lilia maliar","profile_url":"https://gc-cuny.academia.edu/liliamaliar?f_ri=725","photo":"https://0.academia-photos.com/98666670/26811480/25287815/s65_lilia.maliar.jpg"}],"research_interests":[{"id":422,"name":"Computer Science","url":"https://www.academia.edu/Documents/in/Computer_Science?f_ri=725","nofollow":true},{"id":725,"name":"Computational Economics","url":"https://www.academia.edu/Documents/in/Computational_Economics?f_ri=725","nofollow":true},{"id":747,"name":"Econometrics","url":"https://www.academia.edu/Documents/in/Econometrics?f_ri=725","nofollow":true},{"id":3079415,"name":"Finance and Investment Banking","url":"https://www.academia.edu/Documents/in/Finance_and_Investment_Banking?f_ri=725","nofollow":true}]}, }) } })();</script></ul></li></ul></div></div><div class="u-borderBottom1 u-borderColorGrayLighter"><div class="clearfix u-pv7x u-mb0x js-work-card work_3429544" data-work_id="3429544" itemscope="itemscope" itemtype="https://schema.org/ScholarlyArticle"><div class="header"><div class="title u-fontSerif u-fs22 u-lineHeight1_3"><a class="u-tcGrayDarkest js-work-link" href="https://www.academia.edu/3429544/Modeling_and_Simulation_of_an_Artificial_Stock_Option_Market">Modeling and Simulation of an Artificial Stock Option Market</a></div></div><div class="u-pb4x u-mt3x"><div class="summary u-fs14 u-fw300 u-lineHeight1_5 u-tcGrayDarkest"><div class="summarized">Since their introduction in 1973, options have become an important and very popular financial instrument. However, despite much research performed on the subject, the effects of option trading on the underlying asset market are still... <a class="more_link u-tcGrayDark u-linkUnstyled" data-container=".work_3429544" data-show=".complete" data-hide=".summarized" data-more-link-behavior="true" href="#">more</a></div><div class="complete hidden">Since their introduction in 1973, options have become an important and very popular financial instrument. However, despite much research performed on the subject, the effects of option trading on the underlying asset market are still debated. Both empirical and theoretical studies have failed to point out how price volatility and volumes of the underlying asset are affected. In this paper we present the first study on the effects of an option market related to an underlying stock market, using an artificial financial market based on heterogeneous agents. We modeled a realistic European option using two market models. The microstructure of the first model is kept as simple as possible, being composed only of random traders. The second model is more complex and realistic, involving the presence of various kinds of trading strategies (random, fundamentalist and chartist). We show that the introduction of options, in the proposed models, tends to decrease the volatility of the underlying stock price. Moreover, the traders’ wealth can be strongly affected by the use of option hedging.</div></div></div><ul class="InlineList u-ph0x u-fs13"><li class="InlineList-item logged_in_only"><div class="share_on_academia_work_button"><a class="academia_share Button Button--inverseBlue Button--sm js-bookmark-button" data-academia-share="Work/3429544" data-share-source="work_strip" data-spinner="small_white_hide_contents"><i class="fa fa-plus"></i><span class="work-strip-link-text u-ml1x" data-content="button_text">Bookmark</span></a></div></li><li class="InlineList-item"><div class="download"><a id="a3010254efa9757af9c138c131922a70" rel="nofollow" data-download="{"attachment_id":50283170,"asset_id":3429544,"asset_type":"Work","always_allow_download":false,"track":null,"button_location":"work_strip","source":null,"hide_modal":null}" class="Button Button--sm Button--inverseGreen js-download-button prompt_button doc_download" href="https://www.academia.edu/attachments/50283170/download_file?st=MTc0MDU1NDU5OSw4LjIyMi4yMDguMTQ2&s=work_strip"><i class="fa fa-arrow-circle-o-down fa-lg"></i><span class="u-textUppercase u-ml1x" data-content="button_text">Download</span></a></div></li><li class="InlineList-item"><ul class="InlineList InlineList--bordered u-ph0x"><li class="InlineList-item InlineList-item--bordered"><span class="InlineList-item-text">by <span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a class="u-tcGrayDark u-fw700" data-has-card-for-user="263859" href="https://unica.academia.edu/MicheleMarchesi">Michele Marchesi</a><script data-card-contents-for-user="263859" type="text/json">{"id":263859,"first_name":"Michele","last_name":"Marchesi","domain_name":"unica","page_name":"MicheleMarchesi","display_name":"Michele Marchesi","profile_url":"https://unica.academia.edu/MicheleMarchesi?f_ri=725","photo":"https://0.academia-photos.com/263859/64953/71576/s65_michele.marchesi.jpg"}</script></span></span></li><li class="js-paper-rank-work_3429544 InlineList-item InlineList-item--bordered hidden"><span class="js-paper-rank-view hidden u-tcGrayDark" data-paper-rank-work-id="3429544"><i class="u-m1x fa fa-bar-chart"></i><strong class="js-paper-rank"></strong></span><script>$(function() { new Works.PaperRankView({ workId: 3429544, container: ".js-paper-rank-work_3429544", }); });</script></li><li class="js-percentile-work_3429544 InlineList-item InlineList-item--bordered hidden u-tcGrayDark"><span class="percentile-widget hidden"><span class="u-mr2x percentile-widget" style="display: none">•</span><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 3429544; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-percentile-work_3429544"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></li><li class="js-view-count-work_3429544 InlineList-item InlineList-item--bordered hidden"><div><span><span class="js-view-count view-count u-mr2x" data-work-id="3429544"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 3429544; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=3429544]").text(description); $(".js-view-count-work_3429544").attr('title', description).tooltip(); }); });</script></span><script>$(function() { $(".js-view-count-work_3429544").removeClass('hidden') })</script></div></li><li class="InlineList-item u-positionRelative" style="max-width: 250px"><div class="u-positionAbsolute" data-has-card-for-ri-list="3429544"><i class="fa fa-tag InlineList-item-icon u-positionRelative"></i>  <a class="InlineList-item-text u-positionRelative">12</a>  </div><span class="InlineList-item-text u-textTruncate u-pl10x"><a class="InlineList-item-text" data-has-card-for-ri="725" rel="nofollow" href="https://www.academia.edu/Documents/in/Computational_Economics">Computational Economics</a>, <script data-card-contents-for-ri="725" type="text/json">{"id":725,"name":"Computational Economics","url":"https://www.academia.edu/Documents/in/Computational_Economics?f_ri=725","nofollow":true}</script><a class="InlineList-item-text" data-has-card-for-ri="747" rel="nofollow" href="https://www.academia.edu/Documents/in/Econometrics">Econometrics</a>, <script data-card-contents-for-ri="747" type="text/json">{"id":747,"name":"Econometrics","url":"https://www.academia.edu/Documents/in/Econometrics?f_ri=725","nofollow":true}</script><a class="InlineList-item-text" data-has-card-for-ri="11820" rel="nofollow" href="https://www.academia.edu/Documents/in/Modeling_and_Simulation">Modeling and Simulation</a>, <script data-card-contents-for-ri="11820" type="text/json">{"id":11820,"name":"Modeling and Simulation","url":"https://www.academia.edu/Documents/in/Modeling_and_Simulation?f_ri=725","nofollow":true}</script><a class="InlineList-item-text" data-has-card-for-ri="29156" rel="nofollow" href="https://www.academia.edu/Documents/in/Stock_Market">Stock Market</a><script data-card-contents-for-ri="29156" type="text/json">{"id":29156,"name":"Stock Market","url":"https://www.academia.edu/Documents/in/Stock_Market?f_ri=725","nofollow":true}</script></span></li><script>(function(){ if (true) { new Aedu.ResearchInterestListCard({ el: $('*[data-has-card-for-ri-list=3429544]'), work: {"id":3429544,"title":"Modeling and Simulation of an Artificial Stock Option Market","created_at":"2013-04-30T05:20:57.015-07:00","url":"https://www.academia.edu/3429544/Modeling_and_Simulation_of_an_Artificial_Stock_Option_Market?f_ri=725","dom_id":"work_3429544","summary":"Since their introduction in 1973, options have become an important and very popular financial instrument. However, despite much research performed on the subject, the effects of option trading on the underlying asset market are still debated. Both empirical and theoretical studies have failed to point out how price volatility and volumes of the underlying asset are affected. In this paper we present the first study on the effects of an option market related to an underlying stock market, using an artificial financial market based on heterogeneous agents. We modeled a realistic European option using two market models. The microstructure of the first model is kept as simple as possible, being composed only of random traders. The second model is more complex and realistic, involving the presence of various kinds of trading strategies (random, fundamentalist and chartist). We show that the introduction of options, in the proposed models, tends to decrease the volatility of the underlying stock price. Moreover, the traders’ wealth can be strongly affected by the use of option hedging.","downloadable_attachments":[{"id":50283170,"asset_id":3429544,"asset_type":"Work","always_allow_download":false}],"ordered_authors":[{"id":263859,"first_name":"Michele","last_name":"Marchesi","domain_name":"unica","page_name":"MicheleMarchesi","display_name":"Michele Marchesi","profile_url":"https://unica.academia.edu/MicheleMarchesi?f_ri=725","photo":"https://0.academia-photos.com/263859/64953/71576/s65_michele.marchesi.jpg"}],"research_interests":[{"id":725,"name":"Computational Economics","url":"https://www.academia.edu/Documents/in/Computational_Economics?f_ri=725","nofollow":true},{"id":747,"name":"Econometrics","url":"https://www.academia.edu/Documents/in/Econometrics?f_ri=725","nofollow":true},{"id":11820,"name":"Modeling and Simulation","url":"https://www.academia.edu/Documents/in/Modeling_and_Simulation?f_ri=725","nofollow":true},{"id":29156,"name":"Stock Market","url":"https://www.academia.edu/Documents/in/Stock_Market?f_ri=725","nofollow":true},{"id":214983,"name":"Heterogeneous Agents","url":"https://www.academia.edu/Documents/in/Heterogeneous_Agents?f_ri=725"},{"id":270673,"name":"Financial Market","url":"https://www.academia.edu/Documents/in/Financial_Market?f_ri=725"},{"id":370993,"name":"Price Volatility","url":"https://www.academia.edu/Documents/in/Price_Volatility?f_ri=725"},{"id":473797,"name":"Microstructures","url":"https://www.academia.edu/Documents/in/Microstructures?f_ri=725"},{"id":489225,"name":"Stock Price","url":"https://www.academia.edu/Documents/in/Stock_Price?f_ri=725"},{"id":662210,"name":"Stock Options","url":"https://www.academia.edu/Documents/in/Stock_Options?f_ri=725"},{"id":1219400,"name":"Asset Market","url":"https://www.academia.edu/Documents/in/Asset_Market?f_ri=725"},{"id":2036700,"name":"Trading Strategy","url":"https://www.academia.edu/Documents/in/Trading_Strategy?f_ri=725"}]}, }) } })();</script></ul></li></ul></div></div><div class="u-borderBottom1 u-borderColorGrayLighter"><div class="clearfix u-pv7x u-mb0x js-work-card work_3851456" data-work_id="3851456" itemscope="itemscope" itemtype="https://schema.org/ScholarlyArticle"><div class="header"><div class="title u-fontSerif u-fs22 u-lineHeight1_3"><a class="u-tcGrayDarkest js-work-link" href="https://www.academia.edu/3851456/On_Applying_Parallel_Programming_in_Economics">On Applying Parallel Programming in Economics</a></div></div><div class="u-pb4x u-mt3x"><div class="summary u-fs14 u-fw300 u-lineHeight1_5 u-tcGrayDarkest"><div class="summarized">The extent to which parallel programming techniques can be applied in the field of economics is investigated. In particular, some basic parallel programming theory is introduced, followed by an application to a representative economic... <a class="more_link u-tcGrayDark u-linkUnstyled" data-container=".work_3851456" data-show=".complete" data-hide=".summarized" data-more-link-behavior="true" href="#">more</a></div><div class="complete hidden">The extent to which parallel programming techniques can be applied in the field of economics is investigated. In particular, some basic parallel programming theory is introduced, followed by an application to a representative economic model by Aldrich et al. We show that one can incrementally introduce parallelism into a simple serial algorithm, using some simple directives in the source code. The algorithm's runtime is measured and compared for various congurations. We observe a speedup of up to 17x and conclude that parallel programming can indeed be applied in the field of economics, with interesting results.</div></div></div><ul class="InlineList u-ph0x u-fs13"><li class="InlineList-item logged_in_only"><div class="share_on_academia_work_button"><a class="academia_share Button Button--inverseBlue Button--sm js-bookmark-button" data-academia-share="Work/3851456" data-share-source="work_strip" data-spinner="small_white_hide_contents"><i class="fa fa-plus"></i><span class="work-strip-link-text u-ml1x" data-content="button_text">Bookmark</span></a></div></li><li class="InlineList-item"><div class="download"><a id="0219ad7ad74aae4cd2b863da86f3bbfa" rel="nofollow" data-download="{"attachment_id":31495165,"asset_id":3851456,"asset_type":"Work","always_allow_download":false,"track":null,"button_location":"work_strip","source":null,"hide_modal":null}" class="Button Button--sm Button--inverseGreen js-download-button prompt_button doc_download" href="https://www.academia.edu/attachments/31495165/download_file?st=MTc0MDU1NDU5OSw4LjIyMi4yMDguMTQ2&s=work_strip"><i class="fa fa-arrow-circle-o-down fa-lg"></i><span class="u-textUppercase u-ml1x" data-content="button_text">Download</span></a></div></li><li class="InlineList-item"><ul class="InlineList InlineList--bordered u-ph0x"><li class="InlineList-item InlineList-item--bordered"><span class="InlineList-item-text">by <span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a class="u-tcGrayDark u-fw700" data-has-card-for-user="3947075" href="https://ethz.academia.edu/LaurentOberholzer">Laurent Oberholzer</a><script data-card-contents-for-user="3947075" type="text/json">{"id":3947075,"first_name":"Laurent","last_name":"Oberholzer","domain_name":"ethz","page_name":"LaurentOberholzer","display_name":"Laurent Oberholzer","profile_url":"https://ethz.academia.edu/LaurentOberholzer?f_ri=725","photo":"/images/s65_no_pic.png"}</script></span></span></li><li class="js-paper-rank-work_3851456 InlineList-item InlineList-item--bordered hidden"><span class="js-paper-rank-view hidden u-tcGrayDark" data-paper-rank-work-id="3851456"><i class="u-m1x fa fa-bar-chart"></i><strong class="js-paper-rank"></strong></span><script>$(function() { new Works.PaperRankView({ workId: 3851456, container: ".js-paper-rank-work_3851456", }); });</script></li><li class="js-percentile-work_3851456 InlineList-item InlineList-item--bordered hidden u-tcGrayDark"><span class="percentile-widget hidden"><span class="u-mr2x percentile-widget" style="display: none">•</span><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 3851456; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-percentile-work_3851456"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></li><li class="js-view-count-work_3851456 InlineList-item InlineList-item--bordered hidden"><div><span><span class="js-view-count view-count u-mr2x" data-work-id="3851456"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 3851456; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=3851456]").text(description); $(".js-view-count-work_3851456").attr('title', description).tooltip(); }); });</script></span><script>$(function() { $(".js-view-count-work_3851456").removeClass('hidden') })</script></div></li><li class="InlineList-item u-positionRelative" style="max-width: 250px"><div class="u-positionAbsolute" data-has-card-for-ri-list="3851456"><i class="fa fa-tag InlineList-item-icon u-positionRelative"></i>  <a class="InlineList-item-text u-positionRelative">10</a>  </div><span class="InlineList-item-text u-textTruncate u-pl10x"><a class="InlineList-item-text" data-has-card-for-ri="422" rel="nofollow" href="https://www.academia.edu/Documents/in/Computer_Science">Computer Science</a>, <script data-card-contents-for-ri="422" type="text/json">{"id":422,"name":"Computer Science","url":"https://www.academia.edu/Documents/in/Computer_Science?f_ri=725","nofollow":true}</script><a class="InlineList-item-text" data-has-card-for-ri="431" rel="nofollow" href="https://www.academia.edu/Documents/in/Parallel_Algorithms">Parallel Algorithms</a>, <script data-card-contents-for-ri="431" type="text/json">{"id":431,"name":"Parallel Algorithms","url":"https://www.academia.edu/Documents/in/Parallel_Algorithms?f_ri=725","nofollow":true}</script><a class="InlineList-item-text" data-has-card-for-ri="442" rel="nofollow" href="https://www.academia.edu/Documents/in/Parallel_Computing">Parallel Computing</a>, <script data-card-contents-for-ri="442" type="text/json">{"id":442,"name":"Parallel Computing","url":"https://www.academia.edu/Documents/in/Parallel_Computing?f_ri=725","nofollow":true}</script><a class="InlineList-item-text" data-has-card-for-ri="724" rel="nofollow" href="https://www.academia.edu/Documents/in/Economics">Economics</a><script data-card-contents-for-ri="724" type="text/json">{"id":724,"name":"Economics","url":"https://www.academia.edu/Documents/in/Economics?f_ri=725","nofollow":true}</script></span></li><script>(function(){ if (true) { new Aedu.ResearchInterestListCard({ el: $('*[data-has-card-for-ri-list=3851456]'), work: {"id":3851456,"title":"On Applying Parallel Programming in Economics","created_at":"2013-07-03T21:37:44.580-07:00","url":"https://www.academia.edu/3851456/On_Applying_Parallel_Programming_in_Economics?f_ri=725","dom_id":"work_3851456","summary":"The extent to which parallel programming techniques can be applied in the \ffield of economics is investigated. In particular, some basic parallel programming theory is introduced, followed by an application to a representative economic model by Aldrich et al. We show that one can incrementally introduce parallelism into a simple serial algorithm, using some simple directives in the source code. The algorithm's runtime is measured and compared for various con\fgurations. We observe a speedup of up to 17x\u0002 and conclude that parallel programming can indeed be applied in the fi\feld of economics, with interesting results.","downloadable_attachments":[{"id":31495165,"asset_id":3851456,"asset_type":"Work","always_allow_download":false}],"ordered_authors":[{"id":3947075,"first_name":"Laurent","last_name":"Oberholzer","domain_name":"ethz","page_name":"LaurentOberholzer","display_name":"Laurent Oberholzer","profile_url":"https://ethz.academia.edu/LaurentOberholzer?f_ri=725","photo":"/images/s65_no_pic.png"}],"research_interests":[{"id":422,"name":"Computer Science","url":"https://www.academia.edu/Documents/in/Computer_Science?f_ri=725","nofollow":true},{"id":431,"name":"Parallel Algorithms","url":"https://www.academia.edu/Documents/in/Parallel_Algorithms?f_ri=725","nofollow":true},{"id":442,"name":"Parallel Computing","url":"https://www.academia.edu/Documents/in/Parallel_Computing?f_ri=725","nofollow":true},{"id":724,"name":"Economics","url":"https://www.academia.edu/Documents/in/Economics?f_ri=725","nofollow":true},{"id":725,"name":"Computational Economics","url":"https://www.academia.edu/Documents/in/Computational_Economics?f_ri=725"},{"id":3069,"name":"Parallel Programming","url":"https://www.academia.edu/Documents/in/Parallel_Programming?f_ri=725"},{"id":17167,"name":"Parallel Processing","url":"https://www.academia.edu/Documents/in/Parallel_Processing?f_ri=725"},{"id":30157,"name":"C++ Programming","url":"https://www.academia.edu/Documents/in/C_Programming?f_ri=725"},{"id":150326,"name":"Macroeconomics (Business cycles, Nominal and real rigidities, DSGE models)","url":"https://www.academia.edu/Documents/in/Macroeconomics_Business_cycles_Nominal_and_real_rigidities_DSGE_models_?f_ri=725"},{"id":765777,"name":"Parallel Architectures","url":"https://www.academia.edu/Documents/in/Parallel_Architectures?f_ri=725"}]}, }) } })();</script></ul></li></ul></div></div><div class="u-borderBottom1 u-borderColorGrayLighter"><div class="clearfix u-pv7x u-mb0x js-work-card work_47282477" data-work_id="47282477" itemscope="itemscope" itemtype="https://schema.org/ScholarlyArticle"><div class="header"><div class="title u-fontSerif u-fs22 u-lineHeight1_3"><a class="u-tcGrayDarkest js-work-link" href="https://www.academia.edu/47282477/Applied_Computational_Economics_and_Finance">Applied Computational Economics and Finance</a></div></div><div class="u-pb4x u-mt3x"><div class="summary u-fs14 u-fw300 u-lineHeight1_5 u-tcGrayDarkest"><div class="summarized">This is an important book that will influence future research on R&D and innovation. It brings together a number of pioneering papers by Adam Jaffe and Manuel Trajtenberg (and various co-authors) on the use of patent citations to study... <a class="more_link u-tcGrayDark u-linkUnstyled" data-container=".work_47282477" data-show=".complete" data-hide=".summarized" data-more-link-behavior="true" href="#">more</a></div><div class="complete hidden">This is an important book that will influence future research on R&D and innovation. It brings together a number of pioneering papers by Adam Jaffe and Manuel Trajtenberg (and various co-authors) on the use of patent citations to study the innovation process, plus several new pieces of work. The book is organised in four parts. The papers in Part 1 lay the 'conceptual' groundwork for research on patent citations. The first is the classic paper by Trajtenberg demonstrating that citations are linked to demand-based measures of social surplus for one important medical innovation, CT scanners. Making this link between patent citations and social (and private) value provides powerful justification for using citations in economic studies. It is surprising and unfortunate that there have not been similar studies on other innovations, despite the huge growth of empirical work on vertically differentiated product markets.</div></div></div><ul class="InlineList u-ph0x u-fs13"><li class="InlineList-item logged_in_only"><div class="share_on_academia_work_button"><a class="academia_share Button Button--inverseBlue Button--sm js-bookmark-button" data-academia-share="Work/47282477" data-share-source="work_strip" data-spinner="small_white_hide_contents"><i class="fa fa-plus"></i><span class="work-strip-link-text u-ml1x" data-content="button_text">Bookmark</span></a></div></li><li class="InlineList-item"><div class="download"><a id="ae47c928b2dd221fd89994fc76c6415f" rel="nofollow" data-download="{"attachment_id":66457094,"asset_id":47282477,"asset_type":"Work","always_allow_download":false,"track":null,"button_location":"work_strip","source":null,"hide_modal":null}" class="Button Button--sm Button--inverseGreen js-download-button prompt_button doc_download" href="https://www.academia.edu/attachments/66457094/download_file?st=MTc0MDU1NDU5OSw4LjIyMi4yMDguMTQ2&s=work_strip"><i class="fa fa-arrow-circle-o-down fa-lg"></i><span class="u-textUppercase u-ml1x" data-content="button_text">Download</span></a></div></li><li class="InlineList-item"><ul class="InlineList InlineList--bordered u-ph0x"><li class="InlineList-item InlineList-item--bordered"><span class="InlineList-item-text">by <span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a class="u-tcGrayDark u-fw700" data-has-card-for-user="35403164" href="https://independent.academia.edu/PaulFackler">Paul Fackler</a><script data-card-contents-for-user="35403164" type="text/json">{"id":35403164,"first_name":"Paul","last_name":"Fackler","domain_name":"independent","page_name":"PaulFackler","display_name":"Paul Fackler","profile_url":"https://independent.academia.edu/PaulFackler?f_ri=725","photo":"/images/s65_no_pic.png"}</script></span></span></li><li class="js-paper-rank-work_47282477 InlineList-item InlineList-item--bordered hidden"><span class="js-paper-rank-view hidden u-tcGrayDark" data-paper-rank-work-id="47282477"><i class="u-m1x fa fa-bar-chart"></i><strong class="js-paper-rank"></strong></span><script>$(function() { new Works.PaperRankView({ workId: 47282477, container: ".js-paper-rank-work_47282477", }); });</script></li><li class="js-percentile-work_47282477 InlineList-item InlineList-item--bordered hidden u-tcGrayDark"><span class="percentile-widget hidden"><span class="u-mr2x percentile-widget" style="display: none">•</span><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 47282477; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-percentile-work_47282477"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></li><li class="js-view-count-work_47282477 InlineList-item InlineList-item--bordered hidden"><div><span><span class="js-view-count view-count u-mr2x" data-work-id="47282477"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 47282477; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=47282477]").text(description); $(".js-view-count-work_47282477").attr('title', description).tooltip(); }); });</script></span><script>$(function() { $(".js-view-count-work_47282477").removeClass('hidden') })</script></div></li><li class="InlineList-item u-positionRelative" style="max-width: 250px"><div class="u-positionAbsolute" data-has-card-for-ri-list="47282477"><i class="fa fa-tag InlineList-item-icon u-positionRelative"></i>  <a class="InlineList-item-text u-positionRelative">14</a>  </div><span class="InlineList-item-text u-textTruncate u-pl10x"><a class="InlineList-item-text" data-has-card-for-ri="724" rel="nofollow" href="https://www.academia.edu/Documents/in/Economics">Economics</a>, <script data-card-contents-for-ri="724" type="text/json">{"id":724,"name":"Economics","url":"https://www.academia.edu/Documents/in/Economics?f_ri=725","nofollow":true}</script><a class="InlineList-item-text" data-has-card-for-ri="725" rel="nofollow" href="https://www.academia.edu/Documents/in/Computational_Economics">Computational Economics</a>, <script data-card-contents-for-ri="725" type="text/json">{"id":725,"name":"Computational Economics","url":"https://www.academia.edu/Documents/in/Computational_Economics?f_ri=725","nofollow":true}</script><a class="InlineList-item-text" data-has-card-for-ri="747" rel="nofollow" href="https://www.academia.edu/Documents/in/Econometrics">Econometrics</a>, <script data-card-contents-for-ri="747" type="text/json">{"id":747,"name":"Econometrics","url":"https://www.academia.edu/Documents/in/Econometrics?f_ri=725","nofollow":true}</script><a class="InlineList-item-text" data-has-card-for-ri="892" rel="nofollow" href="https://www.academia.edu/Documents/in/Statistics">Statistics</a><script data-card-contents-for-ri="892" type="text/json">{"id":892,"name":"Statistics","url":"https://www.academia.edu/Documents/in/Statistics?f_ri=725","nofollow":true}</script></span></li><script>(function(){ if (true) { new Aedu.ResearchInterestListCard({ el: $('*[data-has-card-for-ri-list=47282477]'), work: {"id":47282477,"title":"Applied Computational Economics and Finance","created_at":"2021-04-21T10:17:59.974-07:00","url":"https://www.academia.edu/47282477/Applied_Computational_Economics_and_Finance?f_ri=725","dom_id":"work_47282477","summary":"This is an important book that will influence future research on R\u0026D and innovation. It brings together a number of pioneering papers by Adam Jaffe and Manuel Trajtenberg (and various co-authors) on the use of patent citations to study the innovation process, plus several new pieces of work. The book is organised in four parts. The papers in Part 1 lay the 'conceptual' groundwork for research on patent citations. The first is the classic paper by Trajtenberg demonstrating that citations are linked to demand-based measures of social surplus for one important medical innovation, CT scanners. Making this link between patent citations and social (and private) value provides powerful justification for using citations in economic studies. It is surprising and unfortunate that there have not been similar studies on other innovations, despite the huge growth of empirical work on vertically differentiated product markets.","downloadable_attachments":[{"id":66457094,"asset_id":47282477,"asset_type":"Work","always_allow_download":false}],"ordered_authors":[{"id":35403164,"first_name":"Paul","last_name":"Fackler","domain_name":"independent","page_name":"PaulFackler","display_name":"Paul Fackler","profile_url":"https://independent.academia.edu/PaulFackler?f_ri=725","photo":"/images/s65_no_pic.png"}],"research_interests":[{"id":724,"name":"Economics","url":"https://www.academia.edu/Documents/in/Economics?f_ri=725","nofollow":true},{"id":725,"name":"Computational Economics","url":"https://www.academia.edu/Documents/in/Computational_Economics?f_ri=725","nofollow":true},{"id":747,"name":"Econometrics","url":"https://www.academia.edu/Documents/in/Econometrics?f_ri=725","nofollow":true},{"id":892,"name":"Statistics","url":"https://www.academia.edu/Documents/in/Statistics?f_ri=725","nofollow":true},{"id":30880,"name":"Numerical Methods","url":"https://www.academia.edu/Documents/in/Numerical_Methods?f_ri=725"},{"id":32149,"name":"Numerical Method","url":"https://www.academia.edu/Documents/in/Numerical_Method?f_ri=725"},{"id":80414,"name":"Mathematical Sciences","url":"https://www.academia.edu/Documents/in/Mathematical_Sciences?f_ri=725"},{"id":171894,"name":"Computers and Mathematics with Applications 59 (2010) 35783582","url":"https://www.academia.edu/Documents/in/Computers_and_Mathematics_with_Applications_59_2010_35783582?f_ri=725"},{"id":213802,"name":"Rational Expectation","url":"https://www.academia.edu/Documents/in/Rational_Expectation?f_ri=725"},{"id":245193,"name":"Numerical Integration","url":"https://www.academia.edu/Documents/in/Numerical_Integration?f_ri=725"},{"id":506482,"name":"Function approximation","url":"https://www.academia.edu/Documents/in/Function_approximation?f_ri=725"},{"id":871199,"name":"Stochastic Model","url":"https://www.academia.edu/Documents/in/Stochastic_Model?f_ri=725"},{"id":1449632,"name":"Computational Method","url":"https://www.academia.edu/Documents/in/Computational_Method?f_ri=725"},{"id":3115632,"name":"Continuous time","url":"https://www.academia.edu/Documents/in/Continuous_time?f_ri=725"}]}, }) } })();</script></ul></li></ul></div></div><div class="u-borderBottom1 u-borderColorGrayLighter"><div class="clearfix u-pv7x u-mb0x js-work-card work_39113839 coauthored" data-work_id="39113839" itemscope="itemscope" itemtype="https://schema.org/ScholarlyArticle"><div class="header"><div class="title u-fontSerif u-fs22 u-lineHeight1_3"><a class="u-tcGrayDarkest js-work-link" href="https://www.academia.edu/39113839/On_the_connection_between_agent_based_simulation_and_methodological_individualism">On the connection between agent-based simulation and methodological individualism</a></div></div><div class="u-pb4x u-mt3x"><div class="summary u-fs14 u-fw300 u-lineHeight1_5 u-tcGrayDarkest"><div class="summarized">This paper investigates the relationship between methodological individualism (MI) and agent-based simulation (ABS). We use a thesis defended by Caterina Marchionni and Petri Ylikoski (2013) as the starting point of our approach.... <a class="more_link u-tcGrayDark u-linkUnstyled" data-container=".work_39113839" data-show=".complete" data-hide=".summarized" data-more-link-behavior="true" href="#">more</a></div><div class="complete hidden">This paper investigates the relationship between methodological individualism (MI) and agent-based simulation (ABS). We use a thesis defended by Caterina Marchionni and Petri Ylikoski (2013) as the starting point of our approach. According to this thesis, since MI is often considered to be a reductionist orientation, it is confusing and meaningless to assume that ABS, which is a non-reductionist and emergentist explanatory model, is committed to MI. We criticise this view and focus on the problem of the proper definition of MI. We explain that MI is compatible with the ABS strategy because reductionism is only the most simplistic variant of MI and argue that ABS explanations must be regarded as explanations in terms of non-reductionist MI.</div></div></div><ul class="InlineList u-ph0x u-fs13"><li class="InlineList-item logged_in_only"><div class="share_on_academia_work_button"><a class="academia_share Button Button--inverseBlue Button--sm js-bookmark-button" data-academia-share="Work/39113839" data-share-source="work_strip" data-spinner="small_white_hide_contents"><i class="fa fa-plus"></i><span class="work-strip-link-text u-ml1x" data-content="button_text">Bookmark</span></a></div></li><li class="InlineList-item"><div class="download"><a id="9f791c42ee14cacb3b1746ecd4d9e448" rel="nofollow" data-download="{"attachment_id":59233825,"asset_id":39113839,"asset_type":"Work","always_allow_download":false,"track":null,"button_location":"work_strip","source":null,"hide_modal":null}" class="Button Button--sm Button--inverseGreen js-download-button prompt_button doc_download" href="https://www.academia.edu/attachments/59233825/download_file?st=MTc0MDU1NDU5OSw4LjIyMi4yMDguMTQ2&s=work_strip"><i class="fa fa-arrow-circle-o-down fa-lg"></i><span class="u-textUppercase u-ml1x" data-content="button_text">Download</span></a></div></li><li class="InlineList-item"><ul class="InlineList InlineList--bordered u-ph0x"><li class="InlineList-item InlineList-item--bordered"><span class="InlineList-item-text">by <span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a class="u-tcGrayDark u-fw700" data-has-card-for-user="4204628" href="https://nankai.academia.edu/FrancescoDiIorio">Francesco Di Iorio</a><script data-card-contents-for-user="4204628" type="text/json">{"id":4204628,"first_name":"Francesco","last_name":"Di Iorio","domain_name":"nankai","page_name":"FrancescoDiIorio","display_name":"Francesco Di Iorio","profile_url":"https://nankai.academia.edu/FrancescoDiIorio?f_ri=725","photo":"https://0.academia-photos.com/4204628/1652631/18725407/s65_francesco.di_iorio.jpg"}</script></span></span><span class="u-displayInlineBlock InlineList-item-text"> and <span class="u-textDecorationUnderline u-clickable InlineList-item-text js-work-more-authors-39113839">+1</span><div class="hidden js-additional-users-39113839"><div><span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a href="https://erenlai.academia.edu/ShuHengChen">Shu-Heng Chen</a></span></div></div></span><script>(function(){ var popoverSettings = { el: $('.js-work-more-authors-39113839'), placement: 'bottom', hide_delay: 200, html: true, content: function(){ return $('.js-additional-users-39113839').html(); } } new HoverPopover(popoverSettings); })();</script></li><li class="js-paper-rank-work_39113839 InlineList-item InlineList-item--bordered hidden"><span class="js-paper-rank-view hidden u-tcGrayDark" data-paper-rank-work-id="39113839"><i class="u-m1x fa fa-bar-chart"></i><strong class="js-paper-rank"></strong></span><script>$(function() { new Works.PaperRankView({ workId: 39113839, container: ".js-paper-rank-work_39113839", }); });</script></li><li class="js-percentile-work_39113839 InlineList-item InlineList-item--bordered hidden u-tcGrayDark"><span class="percentile-widget hidden"><span class="u-mr2x percentile-widget" style="display: none">•</span><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 39113839; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-percentile-work_39113839"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></li><li class="js-view-count-work_39113839 InlineList-item InlineList-item--bordered hidden"><div><span><span class="js-view-count view-count u-mr2x" data-work-id="39113839"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 39113839; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=39113839]").text(description); $(".js-view-count-work_39113839").attr('title', description).tooltip(); }); });</script></span><script>$(function() { $(".js-view-count-work_39113839").removeClass('hidden') })</script></div></li><li class="InlineList-item u-positionRelative" style="max-width: 250px"><div class="u-positionAbsolute" data-has-card-for-ri-list="39113839"><i class="fa fa-tag InlineList-item-icon u-positionRelative"></i>  <a class="InlineList-item-text u-positionRelative">20</a>  </div><span class="InlineList-item-text u-textTruncate u-pl10x"><a class="InlineList-item-text" data-has-card-for-ri="187" rel="nofollow" href="https://www.academia.edu/Documents/in/Computational_Sociology">Computational Sociology</a>, <script data-card-contents-for-ri="187" type="text/json">{"id":187,"name":"Computational Sociology","url":"https://www.academia.edu/Documents/in/Computational_Sociology?f_ri=725","nofollow":true}</script><a class="InlineList-item-text" data-has-card-for-ri="725" rel="nofollow" href="https://www.academia.edu/Documents/in/Computational_Economics">Computational Economics</a>, <script data-card-contents-for-ri="725" type="text/json">{"id":725,"name":"Computational Economics","url":"https://www.academia.edu/Documents/in/Computational_Economics?f_ri=725","nofollow":true}</script><a class="InlineList-item-text" data-has-card-for-ri="1713" rel="nofollow" href="https://www.academia.edu/Documents/in/Austrian_Economics">Austrian Economics</a>, <script data-card-contents-for-ri="1713" type="text/json">{"id":1713,"name":"Austrian Economics","url":"https://www.academia.edu/Documents/in/Austrian_Economics?f_ri=725","nofollow":true}</script><a class="InlineList-item-text" data-has-card-for-ri="2534" rel="nofollow" href="https://www.academia.edu/Documents/in/Multiagent_Systems">Multiagent Systems</a><script data-card-contents-for-ri="2534" type="text/json">{"id":2534,"name":"Multiagent Systems","url":"https://www.academia.edu/Documents/in/Multiagent_Systems?f_ri=725","nofollow":true}</script></span></li><script>(function(){ if (true) { new Aedu.ResearchInterestListCard({ el: $('*[data-has-card-for-ri-list=39113839]'), work: {"id":39113839,"title":"On the connection between agent-based simulation and methodological individualism","created_at":"2019-05-13T04:34:55.987-07:00","url":"https://www.academia.edu/39113839/On_the_connection_between_agent_based_simulation_and_methodological_individualism?f_ri=725","dom_id":"work_39113839","summary":"This paper investigates the relationship between methodological individualism (MI) and agent-based simulation (ABS). We use a thesis defended by Caterina Marchionni and Petri Ylikoski (2013) as the starting point of our approach. According to this thesis, since MI is often considered to be a reductionist orientation, it is confusing and meaningless to assume that ABS, which is a non-reductionist and emergentist explanatory model, is committed to MI. We criticise this view and focus on the problem of the proper definition of MI. We explain that MI is compatible with the ABS strategy because reductionism is only the most simplistic variant of MI and argue that ABS explanations must be regarded as explanations in terms of non-reductionist MI.","downloadable_attachments":[{"id":59233825,"asset_id":39113839,"asset_type":"Work","always_allow_download":false}],"ordered_authors":[{"id":4204628,"first_name":"Francesco","last_name":"Di Iorio","domain_name":"nankai","page_name":"FrancescoDiIorio","display_name":"Francesco Di Iorio","profile_url":"https://nankai.academia.edu/FrancescoDiIorio?f_ri=725","photo":"https://0.academia-photos.com/4204628/1652631/18725407/s65_francesco.di_iorio.jpg"},{"id":12978461,"first_name":"Shu-Heng","last_name":"Chen","domain_name":"erenlai","page_name":"ShuHengChen","display_name":"Shu-Heng Chen","profile_url":"https://erenlai.academia.edu/ShuHengChen?f_ri=725","photo":"/images/s65_no_pic.png"}],"research_interests":[{"id":187,"name":"Computational Sociology","url":"https://www.academia.edu/Documents/in/Computational_Sociology?f_ri=725","nofollow":true},{"id":725,"name":"Computational Economics","url":"https://www.academia.edu/Documents/in/Computational_Economics?f_ri=725","nofollow":true},{"id":1713,"name":"Austrian Economics","url":"https://www.academia.edu/Documents/in/Austrian_Economics?f_ri=725","nofollow":true},{"id":2534,"name":"Multiagent Systems","url":"https://www.academia.edu/Documents/in/Multiagent_Systems?f_ri=725","nofollow":true},{"id":11680,"name":"Social Systems Theory","url":"https://www.academia.edu/Documents/in/Social_Systems_Theory?f_ri=725"},{"id":16117,"name":"Agent-Based Computational Economics","url":"https://www.academia.edu/Documents/in/Agent-Based_Computational_Economics?f_ri=725"},{"id":20177,"name":"Karl Popper","url":"https://www.academia.edu/Documents/in/Karl_Popper?f_ri=725"},{"id":23534,"name":"Individualism","url":"https://www.academia.edu/Documents/in/Individualism?f_ri=725"},{"id":28787,"name":"Nominalism","url":"https://www.academia.edu/Documents/in/Nominalism?f_ri=725"},{"id":34960,"name":"Emergence","url":"https://www.academia.edu/Documents/in/Emergence?f_ri=725"},{"id":34962,"name":"Reductionism","url":"https://www.academia.edu/Documents/in/Reductionism?f_ri=725"},{"id":36957,"name":"Hayek","url":"https://www.academia.edu/Documents/in/Hayek?f_ri=725"},{"id":38890,"name":"Analytical Sociology","url":"https://www.academia.edu/Documents/in/Analytical_Sociology?f_ri=725"},{"id":44638,"name":"Max Weber","url":"https://www.academia.edu/Documents/in/Max_Weber?f_ri=725"},{"id":66768,"name":"Philosophy of the Social Sciences","url":"https://www.academia.edu/Documents/in/Philosophy_of_the_Social_Sciences?f_ri=725"},{"id":97712,"name":"Collectivism \u0026 Individualism","url":"https://www.academia.edu/Documents/in/Collectivism_and_Individualism?f_ri=725"},{"id":134472,"name":"Unintended Consequences","url":"https://www.academia.edu/Documents/in/Unintended_Consequences?f_ri=725"},{"id":135171,"name":"Downward causation","url":"https://www.academia.edu/Documents/in/Downward_causation?f_ri=725"},{"id":209854,"name":"Methodological Individualism","url":"https://www.academia.edu/Documents/in/Methodological_Individualism?f_ri=725"},{"id":308207,"name":"James Coleman","url":"https://www.academia.edu/Documents/in/James_Coleman?f_ri=725"}]}, }) } })();</script></ul></li></ul></div></div><div class="u-borderBottom1 u-borderColorGrayLighter"><div class="clearfix u-pv7x u-mb0x js-work-card work_47557616" data-work_id="47557616" itemscope="itemscope" itemtype="https://schema.org/ScholarlyArticle"><div class="header"><div class="title u-fontSerif u-fs22 u-lineHeight1_3"><a class="u-tcGrayDarkest js-work-link" href="https://www.academia.edu/47557616/On_Social_Learning_and_Robust_Evolutionary_Algorithm_Design_in_the_Cournot_Oligopoly_Game">On Social Learning and Robust Evolutionary Algorithm Design in the Cournot Oligopoly Game</a></div></div><div class="u-pb4x u-mt3x"><div class="summary u-fs14 u-fw300 u-lineHeight1_5 u-tcGrayDarkest"><div class="summarized">Agent-based computational economics (ACE) combines elements from economics and computer science. In this article, the focus is on the relation between the evolutionary technique that is used and the economic problem that is modeled. In... <a class="more_link u-tcGrayDark u-linkUnstyled" data-container=".work_47557616" data-show=".complete" data-hide=".summarized" data-more-link-behavior="true" href="#">more</a></div><div class="complete hidden">Agent-based computational economics (ACE) combines elements from economics and computer science. In this article, the focus is on the relation between the evolutionary technique that is used and the economic problem that is modeled. In the field of ACE, economic simulations often derive parameter settings for the genetic algorithm directly from the values of the economic model parameters.</div></div></div><ul class="InlineList u-ph0x u-fs13"><li class="InlineList-item logged_in_only"><div class="share_on_academia_work_button"><a class="academia_share Button Button--inverseBlue Button--sm js-bookmark-button" data-academia-share="Work/47557616" data-share-source="work_strip" data-spinner="small_white_hide_contents"><i class="fa fa-plus"></i><span class="work-strip-link-text u-ml1x" data-content="button_text">Bookmark</span></a></div></li><li class="InlineList-item"><div class="download"><a id="f89b5fb71e72a646a41bfd6099f33d7a" rel="nofollow" data-download="{"attachment_id":66589295,"asset_id":47557616,"asset_type":"Work","always_allow_download":false,"track":null,"button_location":"work_strip","source":null,"hide_modal":null}" class="Button Button--sm Button--inverseGreen js-download-button prompt_button doc_download" href="https://www.academia.edu/attachments/66589295/download_file?st=MTc0MDU1NDU5OSw4LjIyMi4yMDguMTQ2&s=work_strip"><i class="fa fa-arrow-circle-o-down fa-lg"></i><span class="u-textUppercase u-ml1x" data-content="button_text">Download</span></a></div></li><li class="InlineList-item"><ul class="InlineList InlineList--bordered u-ph0x"><li class="InlineList-item InlineList-item--bordered"><span class="InlineList-item-text">by <span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a class="u-tcGrayDark u-fw700" data-has-card-for-user="64202344" href="https://uva.academia.edu/HansAmman">Hans Amman</a><script data-card-contents-for-user="64202344" type="text/json">{"id":64202344,"first_name":"Hans","last_name":"Amman","domain_name":"uva","page_name":"HansAmman","display_name":"Hans Amman","profile_url":"https://uva.academia.edu/HansAmman?f_ri=725","photo":"https://0.academia-photos.com/64202344/16677059/16967248/s65_hans.amman.jpg"}</script></span></span></li><li class="js-paper-rank-work_47557616 InlineList-item InlineList-item--bordered hidden"><span class="js-paper-rank-view hidden u-tcGrayDark" data-paper-rank-work-id="47557616"><i class="u-m1x fa fa-bar-chart"></i><strong class="js-paper-rank"></strong></span><script>$(function() { new Works.PaperRankView({ workId: 47557616, container: ".js-paper-rank-work_47557616", }); 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$(".js-view-count[data-work-id=47557616]").text(description); $(".js-view-count-work_47557616").attr('title', description).tooltip(); }); });</script></span><script>$(function() { $(".js-view-count-work_47557616").removeClass('hidden') })</script></div></li><li class="InlineList-item u-positionRelative" style="max-width: 250px"><div class="u-positionAbsolute" data-has-card-for-ri-list="47557616"><i class="fa fa-tag InlineList-item-icon u-positionRelative"></i>  <a class="InlineList-item-text u-positionRelative">14</a>  </div><span class="InlineList-item-text u-textTruncate u-pl10x"><a class="InlineList-item-text" data-has-card-for-ri="237" rel="nofollow" href="https://www.academia.edu/Documents/in/Cognitive_Science">Cognitive Science</a>, <script data-card-contents-for-ri="237" type="text/json">{"id":237,"name":"Cognitive Science","url":"https://www.academia.edu/Documents/in/Cognitive_Science?f_ri=725","nofollow":true}</script><a class="InlineList-item-text" data-has-card-for-ri="724" rel="nofollow" href="https://www.academia.edu/Documents/in/Economics">Economics</a>, <script data-card-contents-for-ri="724" type="text/json">{"id":724,"name":"Economics","url":"https://www.academia.edu/Documents/in/Economics?f_ri=725","nofollow":true}</script><a class="InlineList-item-text" data-has-card-for-ri="725" rel="nofollow" href="https://www.academia.edu/Documents/in/Computational_Economics">Computational Economics</a>, <script data-card-contents-for-ri="725" type="text/json">{"id":725,"name":"Computational Economics","url":"https://www.academia.edu/Documents/in/Computational_Economics?f_ri=725","nofollow":true}</script><a class="InlineList-item-text" data-has-card-for-ri="757" rel="nofollow" href="https://www.academia.edu/Documents/in/Game_Theory">Game Theory</a><script data-card-contents-for-ri="757" type="text/json">{"id":757,"name":"Game Theory","url":"https://www.academia.edu/Documents/in/Game_Theory?f_ri=725","nofollow":true}</script></span></li><script>(function(){ if (true) { new Aedu.ResearchInterestListCard({ el: $('*[data-has-card-for-ri-list=47557616]'), work: {"id":47557616,"title":"On Social Learning and Robust Evolutionary Algorithm Design in the Cournot Oligopoly Game","created_at":"2021-04-23T03:24:03.685-07:00","url":"https://www.academia.edu/47557616/On_Social_Learning_and_Robust_Evolutionary_Algorithm_Design_in_the_Cournot_Oligopoly_Game?f_ri=725","dom_id":"work_47557616","summary":"Agent-based computational economics (ACE) combines elements from economics and computer science. In this article, the focus is on the relation between the evolutionary technique that is used and the economic problem that is modeled. In the field of ACE, economic simulations often derive parameter settings for the genetic algorithm directly from the values of the economic model parameters.","downloadable_attachments":[{"id":66589295,"asset_id":47557616,"asset_type":"Work","always_allow_download":false}],"ordered_authors":[{"id":64202344,"first_name":"Hans","last_name":"Amman","domain_name":"uva","page_name":"HansAmman","display_name":"Hans Amman","profile_url":"https://uva.academia.edu/HansAmman?f_ri=725","photo":"https://0.academia-photos.com/64202344/16677059/16967248/s65_hans.amman.jpg"}],"research_interests":[{"id":237,"name":"Cognitive Science","url":"https://www.academia.edu/Documents/in/Cognitive_Science?f_ri=725","nofollow":true},{"id":724,"name":"Economics","url":"https://www.academia.edu/Documents/in/Economics?f_ri=725","nofollow":true},{"id":725,"name":"Computational Economics","url":"https://www.academia.edu/Documents/in/Computational_Economics?f_ri=725","nofollow":true},{"id":757,"name":"Game Theory","url":"https://www.academia.edu/Documents/in/Game_Theory?f_ri=725","nofollow":true},{"id":1701,"name":"Evolutionary algorithms","url":"https://www.academia.edu/Documents/in/Evolutionary_algorithms?f_ri=725"},{"id":3521,"name":"Computational Intelligence","url":"https://www.academia.edu/Documents/in/Computational_Intelligence?f_ri=725"},{"id":3523,"name":"Evolutionary Computation","url":"https://www.academia.edu/Documents/in/Evolutionary_Computation?f_ri=725"},{"id":18961,"name":"Social learning","url":"https://www.academia.edu/Documents/in/Social_learning?f_ri=725"},{"id":30329,"name":"Genetic Algorithm","url":"https://www.academia.edu/Documents/in/Genetic_Algorithm?f_ri=725"},{"id":121035,"name":"Profitability","url":"https://www.academia.edu/Documents/in/Profitability?f_ri=725"},{"id":242997,"name":"Computational","url":"https://www.academia.edu/Documents/in/Computational?f_ri=725"},{"id":265625,"name":"Evolutionary Algorithm","url":"https://www.academia.edu/Documents/in/Evolutionary_Algorithm?f_ri=725"},{"id":536693,"name":"Economic Model","url":"https://www.academia.edu/Documents/in/Economic_Model?f_ri=725"},{"id":1642379,"name":"Nash equilibria","url":"https://www.academia.edu/Documents/in/Nash_equilibria?f_ri=725"}]}, }) } })();</script></ul></li></ul></div></div><div class="u-borderBottom1 u-borderColorGrayLighter"><div class="clearfix u-pv7x u-mb0x js-work-card work_42235963" data-work_id="42235963" itemscope="itemscope" itemtype="https://schema.org/ScholarlyArticle"><div class="header"><div class="title u-fontSerif u-fs22 u-lineHeight1_3"><a class="u-tcGrayDarkest js-work-link" href="https://www.academia.edu/42235963/The_Birth_of_a_Unified_Economics">The Birth of a Unified Economics</a></div></div><div class="u-pb4x u-mt3x"><div class="summary u-fs14 u-fw300 u-lineHeight1_5 u-tcGrayDarkest"><div class="summarized">The paper outlines an original thinking theory and its applications to economics. The author attributes the flaws and divisiveness of economics mainly to the lack of a proper theory on how a person thinks. Human thoughts shall be... <a class="more_link u-tcGrayDark u-linkUnstyled" data-container=".work_42235963" data-show=".complete" data-hide=".summarized" data-more-link-behavior="true" href="#">more</a></div><div class="complete hidden">The paper outlines an original thinking theory and its applications to economics. The author attributes the flaws and divisiveness of economics mainly to the lack of a proper theory on how a person thinks. Human thoughts shall be entities, and thinking shall be behaviors, both featured spatiotemporally. Simulating a computer, human thinking can be Kantianly and dually interpreted as computational Operations which mean that Instructions, as the innate and general thinking tools, process information or data selectively, serially, and “roundaboutly”. Conditioning with Operational speed, time, space and computing economy, the architecture reasonably leads to the results of knowledge stocks, Combinatorial Explosions, subjectivities, pluralities, conflicts, innovations, developments, “Semi-internalization”, convergences, divergences, “High-order Consistency”, etc., and hence a great deal of theoretical socio-economic puzzles are basically solved, including institutions, organizations, money, capital, Invisible Hands, business cycles, crises,  powers, governments, etc. This explosive framework could be a decisive breakthrough and a deconstruction of the mainstream equilibrium paradigm, and hence a grand synthesis or unification and a new comprehensive research program of economics.</div></div></div><ul class="InlineList u-ph0x u-fs13"><li class="InlineList-item logged_in_only"><div class="share_on_academia_work_button"><a class="academia_share Button Button--inverseBlue Button--sm js-bookmark-button" data-academia-share="Work/42235963" data-share-source="work_strip" data-spinner="small_white_hide_contents"><i class="fa fa-plus"></i><span class="work-strip-link-text u-ml1x" data-content="button_text">Bookmark</span></a></div></li><li class="InlineList-item"><div class="download"><a id="7b08b0fa239a10639574cc77c57b2bc0" rel="nofollow" data-download="{"attachment_id":62385774,"asset_id":42235963,"asset_type":"Work","always_allow_download":false,"track":null,"button_location":"work_strip","source":null,"hide_modal":null}" class="Button Button--sm Button--inverseGreen js-download-button prompt_button doc_download" href="https://www.academia.edu/attachments/62385774/download_file?st=MTc0MDU1NDU5OSw4LjIyMi4yMDguMTQ2&s=work_strip"><i class="fa fa-arrow-circle-o-down fa-lg"></i><span class="u-textUppercase u-ml1x" data-content="button_text">Download</span></a></div></li><li class="InlineList-item"><ul class="InlineList InlineList--bordered u-ph0x"><li class="InlineList-item InlineList-item--bordered"><span class="InlineList-item-text">by <span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a class="u-tcGrayDark u-fw700" data-has-card-for-user="144934071" href="https://unc.academia.edu/BinLi">Bin Li</a><script data-card-contents-for-user="144934071" type="text/json">{"id":144934071,"first_name":"Bin","last_name":"Li","domain_name":"unc","page_name":"BinLi","display_name":"Bin Li","profile_url":"https://unc.academia.edu/BinLi?f_ri=725","photo":"https://0.academia-photos.com/144934071/71202806/59642344/s65_bin.li.jpg"}</script></span></span></li><li class="js-paper-rank-work_42235963 InlineList-item InlineList-item--bordered hidden"><span class="js-paper-rank-view hidden u-tcGrayDark" data-paper-rank-work-id="42235963"><i class="u-m1x fa fa-bar-chart"></i><strong class="js-paper-rank"></strong></span><script>$(function() { new Works.PaperRankView({ workId: 42235963, container: ".js-paper-rank-work_42235963", }); 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$(".js-view-count[data-work-id=42235963]").text(description); $(".js-view-count-work_42235963").attr('title', description).tooltip(); }); });</script></span><script>$(function() { $(".js-view-count-work_42235963").removeClass('hidden') })</script></div></li><li class="InlineList-item u-positionRelative" style="max-width: 250px"><div class="u-positionAbsolute" data-has-card-for-ri-list="42235963"><i class="fa fa-tag InlineList-item-icon u-positionRelative"></i>  <a class="InlineList-item-text u-positionRelative">18</a>  </div><span class="InlineList-item-text u-textTruncate u-pl10x"><a class="InlineList-item-text" data-has-card-for-ri="254" rel="nofollow" href="https://www.academia.edu/Documents/in/Emotion">Emotion</a>, <script data-card-contents-for-ri="254" type="text/json">{"id":254,"name":"Emotion","url":"https://www.academia.edu/Documents/in/Emotion?f_ri=725","nofollow":true}</script><a class="InlineList-item-text" data-has-card-for-ri="724" rel="nofollow" href="https://www.academia.edu/Documents/in/Economics">Economics</a>, <script data-card-contents-for-ri="724" type="text/json">{"id":724,"name":"Economics","url":"https://www.academia.edu/Documents/in/Economics?f_ri=725","nofollow":true}</script><a class="InlineList-item-text" data-has-card-for-ri="725" rel="nofollow" href="https://www.academia.edu/Documents/in/Computational_Economics">Computational Economics</a>, <script data-card-contents-for-ri="725" type="text/json">{"id":725,"name":"Computational Economics","url":"https://www.academia.edu/Documents/in/Computational_Economics?f_ri=725","nofollow":true}</script><a class="InlineList-item-text" data-has-card-for-ri="731" rel="nofollow" href="https://www.academia.edu/Documents/in/Evolutionary_Economics">Evolutionary Economics</a><script data-card-contents-for-ri="731" type="text/json">{"id":731,"name":"Evolutionary Economics","url":"https://www.academia.edu/Documents/in/Evolutionary_Economics?f_ri=725","nofollow":true}</script></span></li><script>(function(){ if (true) { new Aedu.ResearchInterestListCard({ el: $('*[data-has-card-for-ri-list=42235963]'), work: {"id":42235963,"title":"The Birth of a Unified Economics","created_at":"2020-03-16T19:04:01.096-07:00","url":"https://www.academia.edu/42235963/The_Birth_of_a_Unified_Economics?f_ri=725","dom_id":"work_42235963","summary":"The paper outlines an original thinking theory and its applications to economics. The author attributes the flaws and divisiveness of economics mainly to the lack of a proper theory on how a person thinks. Human thoughts shall be entities, and thinking shall be behaviors, both featured spatiotemporally. Simulating a computer, human thinking can be Kantianly and dually interpreted as computational Operations which mean that Instructions, as the innate and general thinking tools, process information or data selectively, serially, and “roundaboutly”. Conditioning with Operational speed, time, space and computing economy, the architecture reasonably leads to the results of knowledge stocks, Combinatorial Explosions, subjectivities, pluralities, conflicts, innovations, developments, “Semi-internalization”, convergences, divergences, “High-order Consistency”, etc., and hence a great deal of theoretical socio-economic puzzles are basically solved, including institutions, organizations, money, capital, Invisible Hands, business cycles, crises, powers, governments, etc. This explosive framework could be a decisive breakthrough and a deconstruction of the mainstream equilibrium paradigm, and hence a grand synthesis or unification and a new comprehensive research program of economics.","downloadable_attachments":[{"id":62385774,"asset_id":42235963,"asset_type":"Work","always_allow_download":false}],"ordered_authors":[{"id":144934071,"first_name":"Bin","last_name":"Li","domain_name":"unc","page_name":"BinLi","display_name":"Bin Li","profile_url":"https://unc.academia.edu/BinLi?f_ri=725","photo":"https://0.academia-photos.com/144934071/71202806/59642344/s65_bin.li.jpg"}],"research_interests":[{"id":254,"name":"Emotion","url":"https://www.academia.edu/Documents/in/Emotion?f_ri=725","nofollow":true},{"id":724,"name":"Economics","url":"https://www.academia.edu/Documents/in/Economics?f_ri=725","nofollow":true},{"id":725,"name":"Computational Economics","url":"https://www.academia.edu/Documents/in/Computational_Economics?f_ri=725","nofollow":true},{"id":731,"name":"Evolutionary Economics","url":"https://www.academia.edu/Documents/in/Evolutionary_Economics?f_ri=725","nofollow":true},{"id":750,"name":"Institutional Economics","url":"https://www.academia.edu/Documents/in/Institutional_Economics?f_ri=725"},{"id":764,"name":"Macroeconomics","url":"https://www.academia.edu/Documents/in/Macroeconomics?f_ri=725"},{"id":803,"name":"Philosophy","url":"https://www.academia.edu/Documents/in/Philosophy?f_ri=725"},{"id":951,"name":"Humanities","url":"https://www.academia.edu/Documents/in/Humanities?f_ri=725"},{"id":2065,"name":"Research Methodology","url":"https://www.academia.edu/Documents/in/Research_Methodology?f_ri=725"},{"id":13805,"name":"Behavioral Economics","url":"https://www.academia.edu/Documents/in/Behavioral_Economics?f_ri=725"},{"id":15708,"name":"Bounded Rationality","url":"https://www.academia.edu/Documents/in/Bounded_Rationality?f_ri=725"},{"id":24769,"name":"Chaos/Complexity Theory","url":"https://www.academia.edu/Documents/in/Chaos_Complexity_Theory?f_ri=725"},{"id":26817,"name":"Algorithm","url":"https://www.academia.edu/Documents/in/Algorithm?f_ri=725"},{"id":32938,"name":"Pluralism","url":"https://www.academia.edu/Documents/in/Pluralism?f_ri=725"},{"id":44096,"name":"Knowledge","url":"https://www.academia.edu/Documents/in/Knowledge?f_ri=725"},{"id":48482,"name":"Irrationality","url":"https://www.academia.edu/Documents/in/Irrationality?f_ri=725"},{"id":56710,"name":"Social Engineering","url":"https://www.academia.edu/Documents/in/Social_Engineering?f_ri=725"},{"id":778682,"name":"New thinking in economics","url":"https://www.academia.edu/Documents/in/New_thinking_in_economics?f_ri=725"}]}, }) } })();</script></ul></li></ul></div></div><div class="u-borderBottom1 u-borderColorGrayLighter"><div class="clearfix u-pv7x u-mb0x js-work-card work_32046845" data-work_id="32046845" itemscope="itemscope" itemtype="https://schema.org/ScholarlyArticle"><div class="header"><div class="title u-fontSerif u-fs22 u-lineHeight1_3"><a class="u-tcGrayDarkest js-work-link" href="https://www.academia.edu/32046845/Wavelet_Analysis_of_Commodity_Price_Behavior">Wavelet Analysis of Commodity Price Behavior</a></div></div><div class="u-pb4x u-mt3x"><div class="summary u-fs14 u-fw300 u-lineHeight1_5 u-tcGrayDarkest"><div class="summarized">We propose a form of semi-nonparametric regression based on wavelet analysis. Traditional time series methods usually involve either the time or the frequency domain, but wavelets can combine the information from both of these. While... <a class="more_link u-tcGrayDark u-linkUnstyled" data-container=".work_32046845" data-show=".complete" data-hide=".summarized" data-more-link-behavior="true" href="#">more</a></div><div class="complete hidden">We propose a form of semi-nonparametric regression based on wavelet analysis. Traditional time series methods usually involve either the time or the frequency domain, but wavelets can combine the information from both of these. While wavelet transforms are typically restricted to equally spaced observations an integer power of 2 in number, we show how to go beyond these constraints. We use our methods to construct \patios" for 21 important international commodity price series. These graph the magnitude of the variations in the series at di erent time scales for various subperiods of the full sample.</div></div></div><ul class="InlineList u-ph0x u-fs13"><li class="InlineList-item logged_in_only"><div class="share_on_academia_work_button"><a class="academia_share Button Button--inverseBlue Button--sm js-bookmark-button" data-academia-share="Work/32046845" data-share-source="work_strip" data-spinner="small_white_hide_contents"><i class="fa fa-plus"></i><span class="work-strip-link-text u-ml1x" data-content="button_text">Bookmark</span></a></div></li><li class="InlineList-item"><div class="download"><a id="daca9d92b58efa63389efe675de6efbe" rel="nofollow" data-download="{"attachment_id":52308397,"asset_id":32046845,"asset_type":"Work","always_allow_download":false,"track":null,"button_location":"work_strip","source":null,"hide_modal":null}" class="Button Button--sm Button--inverseGreen js-download-button prompt_button doc_download" href="https://www.academia.edu/attachments/52308397/download_file?st=MTc0MDU1NDU5OSw4LjIyMi4yMDguMTQ2&s=work_strip"><i class="fa fa-arrow-circle-o-down fa-lg"></i><span class="u-textUppercase u-ml1x" data-content="button_text">Download</span></a></div></li><li class="InlineList-item"><ul class="InlineList InlineList--bordered u-ph0x"><li class="InlineList-item InlineList-item--bordered"><span class="InlineList-item-text">by <span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a class="u-tcGrayDark u-fw700" data-has-card-for-user="33782563" href="https://mcgill.academia.edu/RussellDavidson">Russell Davidson</a><script data-card-contents-for-user="33782563" type="text/json">{"id":33782563,"first_name":"Russell","last_name":"Davidson","domain_name":"mcgill","page_name":"RussellDavidson","display_name":"Russell Davidson","profile_url":"https://mcgill.academia.edu/RussellDavidson?f_ri=725","photo":"https://0.academia-photos.com/33782563/46191570/35772552/s65_russell.davidson.jpeg"}</script></span></span></li><li class="js-paper-rank-work_32046845 InlineList-item InlineList-item--bordered hidden"><span class="js-paper-rank-view hidden u-tcGrayDark" data-paper-rank-work-id="32046845"><i class="u-m1x fa fa-bar-chart"></i><strong class="js-paper-rank"></strong></span><script>$(function() { new Works.PaperRankView({ workId: 32046845, container: ".js-paper-rank-work_32046845", }); 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$(".js-view-count[data-work-id=32046845]").text(description); $(".js-view-count-work_32046845").attr('title', description).tooltip(); }); });</script></span><script>$(function() { $(".js-view-count-work_32046845").removeClass('hidden') })</script></div></li><li class="InlineList-item u-positionRelative" style="max-width: 250px"><div class="u-positionAbsolute" data-has-card-for-ri-list="32046845"><i class="fa fa-tag InlineList-item-icon u-positionRelative"></i>  <a class="InlineList-item-text u-positionRelative">7</a>  </div><span class="InlineList-item-text u-textTruncate u-pl9x"><a class="InlineList-item-text" data-has-card-for-ri="725" rel="nofollow" href="https://www.academia.edu/Documents/in/Computational_Economics">Computational Economics</a>, <script data-card-contents-for-ri="725" type="text/json">{"id":725,"name":"Computational Economics","url":"https://www.academia.edu/Documents/in/Computational_Economics?f_ri=725","nofollow":true}</script><a class="InlineList-item-text" data-has-card-for-ri="747" rel="nofollow" href="https://www.academia.edu/Documents/in/Econometrics">Econometrics</a>, <script data-card-contents-for-ri="747" type="text/json">{"id":747,"name":"Econometrics","url":"https://www.academia.edu/Documents/in/Econometrics?f_ri=725","nofollow":true}</script><a class="InlineList-item-text" data-has-card-for-ri="4456" rel="nofollow" href="https://www.academia.edu/Documents/in/Time_Series">Time Series</a>, <script data-card-contents-for-ri="4456" type="text/json">{"id":4456,"name":"Time Series","url":"https://www.academia.edu/Documents/in/Time_Series?f_ri=725","nofollow":true}</script><a class="InlineList-item-text" data-has-card-for-ri="55276" rel="nofollow" href="https://www.academia.edu/Documents/in/Wavelet_Analysis">Wavelet Analysis</a><script data-card-contents-for-ri="55276" type="text/json">{"id":55276,"name":"Wavelet Analysis","url":"https://www.academia.edu/Documents/in/Wavelet_Analysis?f_ri=725","nofollow":true}</script></span></li><script>(function(){ if (true) { new Aedu.ResearchInterestListCard({ el: $('*[data-has-card-for-ri-list=32046845]'), work: {"id":32046845,"title":"Wavelet Analysis of Commodity Price Behavior","created_at":"2017-03-26T00:12:34.662-07:00","url":"https://www.academia.edu/32046845/Wavelet_Analysis_of_Commodity_Price_Behavior?f_ri=725","dom_id":"work_32046845","summary":"We propose a form of semi-nonparametric regression based on wavelet analysis. Traditional time series methods usually involve either the time or the frequency domain, but wavelets can combine the information from both of these. While wavelet transforms are typically restricted to equally spaced observations an integer power of 2 in number, we show how to go beyond these constraints. We use our methods to construct \\patios\" for 21 important international commodity price series. These graph the magnitude of the variations in the series at di erent time scales for various subperiods of the full sample.","downloadable_attachments":[{"id":52308397,"asset_id":32046845,"asset_type":"Work","always_allow_download":false}],"ordered_authors":[{"id":33782563,"first_name":"Russell","last_name":"Davidson","domain_name":"mcgill","page_name":"RussellDavidson","display_name":"Russell Davidson","profile_url":"https://mcgill.academia.edu/RussellDavidson?f_ri=725","photo":"https://0.academia-photos.com/33782563/46191570/35772552/s65_russell.davidson.jpeg"}],"research_interests":[{"id":725,"name":"Computational Economics","url":"https://www.academia.edu/Documents/in/Computational_Economics?f_ri=725","nofollow":true},{"id":747,"name":"Econometrics","url":"https://www.academia.edu/Documents/in/Econometrics?f_ri=725","nofollow":true},{"id":4456,"name":"Time Series","url":"https://www.academia.edu/Documents/in/Time_Series?f_ri=725","nofollow":true},{"id":55276,"name":"Wavelet Analysis","url":"https://www.academia.edu/Documents/in/Wavelet_Analysis?f_ri=725","nofollow":true},{"id":91262,"name":"Wavelet Transform","url":"https://www.academia.edu/Documents/in/Wavelet_Transform?f_ri=725"},{"id":180204,"name":"Nonparametric Regression","url":"https://www.academia.edu/Documents/in/Nonparametric_Regression?f_ri=725"},{"id":1625072,"name":"Frequency Domain","url":"https://www.academia.edu/Documents/in/Frequency_Domain?f_ri=725"}]}, }) } })();</script></ul></li></ul></div></div><div class="u-borderBottom1 u-borderColorGrayLighter"><div class="clearfix u-pv7x u-mb0x js-work-card work_3131240" data-work_id="3131240" itemscope="itemscope" itemtype="https://schema.org/ScholarlyArticle"><div class="header"><div class="title u-fontSerif u-fs22 u-lineHeight1_3"><a class="u-tcGrayDarkest js-work-link" href="https://www.academia.edu/3131240/Agent_Based_Computational_Economics_and_Cognitive_Economics">Agent-Based Computational Economics and Cognitive Economics</a></div></div><div class="u-pb4x u-mt3x"><div class="summary u-fs14 u-fw300 u-lineHeight1_5 u-tcGrayDarkest"><div class="summarized">This paper provides a short introduction to Agent-based Computational Economics (ACE), in order to underline the interest of such an approach in cognitive economics. Section 2 provides a brief bird's eye view of ACE. In section 3, some... <a class="more_link u-tcGrayDark u-linkUnstyled" data-container=".work_3131240" data-show=".complete" data-hide=".summarized" data-more-link-behavior="true" href="#">more</a></div><div class="complete hidden">This paper provides a short introduction to Agent-based Computational Economics (ACE), in order to underline the interest of such an approach in cognitive economics. Section 2 provides a brief bird's eye view of ACE. In section 3, some interesting features of the Santa-Fe Approach to complexity are then introduced by taking simple examples using the Moduleco computational laboratory. Section 4 provides a short introduction to the object-oriented architecture of the Moduleco's framework. Section 5 underlines the interest of ACE for modelling and exploring dynamic features of markets viewed as cognitive and complex social interactive systems. Simple examples of simulations based on two cognitive economics models are briefly discussed. The first one, deals with the so-called exploration-exploitation compromise, while the second deal with social influence and dynamics over social networks .</div></div></div><ul class="InlineList u-ph0x u-fs13"><li class="InlineList-item logged_in_only"><div class="share_on_academia_work_button"><a class="academia_share Button Button--inverseBlue Button--sm js-bookmark-button" data-academia-share="Work/3131240" data-share-source="work_strip" data-spinner="small_white_hide_contents"><i class="fa fa-plus"></i><span class="work-strip-link-text u-ml1x" data-content="button_text">Bookmark</span></a></div></li><li class="InlineList-item"><div class="download"><a id="0258fc515820308c0a5064e41aa6a241" rel="nofollow" data-download="{"attachment_id":31043899,"asset_id":3131240,"asset_type":"Work","always_allow_download":false,"track":null,"button_location":"work_strip","source":null,"hide_modal":null}" class="Button Button--sm Button--inverseGreen js-download-button prompt_button doc_download" href="https://www.academia.edu/attachments/31043899/download_file?st=MTc0MDU1NDU5OSw4LjIyMi4yMDguMTQ2&s=work_strip"><i class="fa fa-arrow-circle-o-down fa-lg"></i><span class="u-textUppercase u-ml1x" data-content="button_text">Download</span></a></div></li><li class="InlineList-item"><ul class="InlineList InlineList--bordered u-ph0x"><li class="InlineList-item InlineList-item--bordered"><span class="InlineList-item-text">by <span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a class="u-tcGrayDark u-fw700" data-has-card-for-user="1170309" href="https://gemass.academia.edu/dphan">Denis PHAN</a><script data-card-contents-for-user="1170309" type="text/json">{"id":1170309,"first_name":"Denis","last_name":"PHAN","domain_name":"gemass","page_name":"dphan","display_name":"Denis PHAN","profile_url":"https://gemass.academia.edu/dphan?f_ri=725","photo":"https://0.academia-photos.com/1170309/3640577/4269709/s65_denis.phan.jpg"}</script></span></span></li><li class="js-paper-rank-work_3131240 InlineList-item InlineList-item--bordered hidden"><span class="js-paper-rank-view hidden u-tcGrayDark" data-paper-rank-work-id="3131240"><i class="u-m1x fa fa-bar-chart"></i><strong class="js-paper-rank"></strong></span><script>$(function() { new Works.PaperRankView({ workId: 3131240, container: ".js-paper-rank-work_3131240", }); 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$(".js-view-count[data-work-id=3131240]").text(description); $(".js-view-count-work_3131240").attr('title', description).tooltip(); }); });</script></span><script>$(function() { $(".js-view-count-work_3131240").removeClass('hidden') })</script></div></li><li class="InlineList-item u-positionRelative" style="max-width: 250px"><div class="u-positionAbsolute" data-has-card-for-ri-list="3131240"><i class="fa fa-tag InlineList-item-icon u-positionRelative"></i>  <a class="InlineList-item-text u-positionRelative">2</a>  </div><span class="InlineList-item-text u-textTruncate u-pl9x"><a class="InlineList-item-text" data-has-card-for-ri="725" rel="nofollow" href="https://www.academia.edu/Documents/in/Computational_Economics">Computational Economics</a>, <script data-card-contents-for-ri="725" type="text/json">{"id":725,"name":"Computational Economics","url":"https://www.academia.edu/Documents/in/Computational_Economics?f_ri=725","nofollow":true}</script><a class="InlineList-item-text" data-has-card-for-ri="30603" rel="nofollow" href="https://www.academia.edu/Documents/in/Social_Influence">Social Influence</a><script data-card-contents-for-ri="30603" type="text/json">{"id":30603,"name":"Social Influence","url":"https://www.academia.edu/Documents/in/Social_Influence?f_ri=725","nofollow":true}</script></span></li><script>(function(){ if (true) { new Aedu.ResearchInterestListCard({ el: $('*[data-has-card-for-ri-list=3131240]'), work: {"id":3131240,"title":"Agent-Based Computational Economics and Cognitive Economics","created_at":"2013-03-27T17:15:22.174-07:00","url":"https://www.academia.edu/3131240/Agent_Based_Computational_Economics_and_Cognitive_Economics?f_ri=725","dom_id":"work_3131240","summary":"This paper provides a short introduction to Agent-based Computational Economics (ACE), in order to underline the interest of such an approach in cognitive economics. Section 2 provides a brief bird's eye view of ACE. In section 3, some interesting features of the Santa-Fe Approach to complexity are then introduced by taking simple examples using the Moduleco computational laboratory. Section 4 provides a short introduction to the object-oriented architecture of the Moduleco's framework. Section 5 underlines the interest of ACE for modelling and exploring dynamic features of markets viewed as cognitive and complex social interactive systems. Simple examples of simulations based on two cognitive economics models are briefly discussed. The first one, deals with the so-called exploration-exploitation compromise, while the second deal with social influence and dynamics over social networks .","downloadable_attachments":[{"id":31043899,"asset_id":3131240,"asset_type":"Work","always_allow_download":false}],"ordered_authors":[{"id":1170309,"first_name":"Denis","last_name":"PHAN","domain_name":"gemass","page_name":"dphan","display_name":"Denis PHAN","profile_url":"https://gemass.academia.edu/dphan?f_ri=725","photo":"https://0.academia-photos.com/1170309/3640577/4269709/s65_denis.phan.jpg"}],"research_interests":[{"id":725,"name":"Computational Economics","url":"https://www.academia.edu/Documents/in/Computational_Economics?f_ri=725","nofollow":true},{"id":30603,"name":"Social Influence","url":"https://www.academia.edu/Documents/in/Social_Influence?f_ri=725","nofollow":true}]}, }) } })();</script></ul></li></ul></div></div><div class="u-borderBottom1 u-borderColorGrayLighter"><div class="clearfix u-pv7x u-mb0x js-work-card work_65625325" data-work_id="65625325" itemscope="itemscope" itemtype="https://schema.org/ScholarlyArticle"><div class="header"><div class="title u-fontSerif u-fs22 u-lineHeight1_3"><a class="u-tcGrayDarkest js-work-link" href="https://www.academia.edu/65625325/Programming_languages_in_economics">Programming languages in economics</a></div></div><div class="u-pb4x u-mt3x"><div class="summary u-fs14 u-fw300 u-lineHeight1_5 u-tcGrayDarkest"><div class="summarized">Young economists sometimes ask which computer programming languages they should learn. This paper answers that question by suggesting that they begin with a high level language like GAUSS, GAMS, Mathematica, Maple or MATLAB depending on... <a class="more_link u-tcGrayDark u-linkUnstyled" data-container=".work_65625325" data-show=".complete" data-hide=".summarized" data-more-link-behavior="true" href="#">more</a></div><div class="complete hidden">Young economists sometimes ask which computer programming languages they should learn. This paper answers that question by suggesting that they begin with a high level language like GAUSS, GAMS, Mathematica, Maple or MATLAB depending on their field of specialization in economics. Then they should work down to one of the low level languages such as Fortran, Basic, C, C++ or Java depending on the planned areas of application. Finally, they should proceed to the languages which are used to develop graphical interfaces and internet applications, viz. Visual Basic,</div></div></div><ul class="InlineList u-ph0x u-fs13"><li class="InlineList-item logged_in_only"><div class="share_on_academia_work_button"><a class="academia_share Button Button--inverseBlue Button--sm js-bookmark-button" data-academia-share="Work/65625325" data-share-source="work_strip" data-spinner="small_white_hide_contents"><i class="fa fa-plus"></i><span class="work-strip-link-text u-ml1x" data-content="button_text">Bookmark</span></a></div></li><li class="InlineList-item"><div class="download"><a id="d2dbc7eb5f88d308ea610075e0d19546" rel="nofollow" data-download="{"attachment_id":77140592,"asset_id":65625325,"asset_type":"Work","always_allow_download":false,"track":null,"button_location":"work_strip","source":null,"hide_modal":null}" class="Button Button--sm Button--inverseGreen js-download-button prompt_button doc_download" href="https://www.academia.edu/attachments/77140592/download_file?st=MTc0MDU1NDU5OSw4LjIyMi4yMDguMTQ2&s=work_strip"><i class="fa fa-arrow-circle-o-down fa-lg"></i><span class="u-textUppercase u-ml1x" data-content="button_text">Download</span></a></div></li><li class="InlineList-item"><ul class="InlineList InlineList--bordered u-ph0x"><li class="InlineList-item InlineList-item--bordered"><span class="InlineList-item-text">by <span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a class="u-tcGrayDark u-fw700" data-has-card-for-user="154963618" href="https://independent.academia.edu/HansAmman">Hans Amman</a><script data-card-contents-for-user="154963618" type="text/json">{"id":154963618,"first_name":"Hans","last_name":"Amman","domain_name":"independent","page_name":"HansAmman","display_name":"Hans Amman","profile_url":"https://independent.academia.edu/HansAmman?f_ri=725","photo":"/images/s65_no_pic.png"}</script></span></span></li><li class="js-paper-rank-work_65625325 InlineList-item InlineList-item--bordered hidden"><span class="js-paper-rank-view hidden u-tcGrayDark" data-paper-rank-work-id="65625325"><i class="u-m1x fa fa-bar-chart"></i><strong class="js-paper-rank"></strong></span><script>$(function() { new Works.PaperRankView({ workId: 65625325, container: ".js-paper-rank-work_65625325", }); 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$(".js-view-count[data-work-id=65625325]").text(description); $(".js-view-count-work_65625325").attr('title', description).tooltip(); }); });</script></span><script>$(function() { $(".js-view-count-work_65625325").removeClass('hidden') })</script></div></li><li class="InlineList-item u-positionRelative" style="max-width: 250px"><div class="u-positionAbsolute" data-has-card-for-ri-list="65625325"><i class="fa fa-tag InlineList-item-icon u-positionRelative"></i>  <a class="InlineList-item-text u-positionRelative">12</a>  </div><span class="InlineList-item-text u-textTruncate u-pl10x"><a class="InlineList-item-text" data-has-card-for-ri="451" rel="nofollow" href="https://www.academia.edu/Documents/in/Programming_Languages">Programming Languages</a>, <script data-card-contents-for-ri="451" type="text/json">{"id":451,"name":"Programming Languages","url":"https://www.academia.edu/Documents/in/Programming_Languages?f_ri=725","nofollow":true}</script><a class="InlineList-item-text" data-has-card-for-ri="724" rel="nofollow" href="https://www.academia.edu/Documents/in/Economics">Economics</a>, <script data-card-contents-for-ri="724" type="text/json">{"id":724,"name":"Economics","url":"https://www.academia.edu/Documents/in/Economics?f_ri=725","nofollow":true}</script><a class="InlineList-item-text" data-has-card-for-ri="725" rel="nofollow" href="https://www.academia.edu/Documents/in/Computational_Economics">Computational Economics</a>, <script data-card-contents-for-ri="725" type="text/json">{"id":725,"name":"Computational Economics","url":"https://www.academia.edu/Documents/in/Computational_Economics?f_ri=725","nofollow":true}</script><a class="InlineList-item-text" data-has-card-for-ri="747" rel="nofollow" href="https://www.academia.edu/Documents/in/Econometrics">Econometrics</a><script data-card-contents-for-ri="747" type="text/json">{"id":747,"name":"Econometrics","url":"https://www.academia.edu/Documents/in/Econometrics?f_ri=725","nofollow":true}</script></span></li><script>(function(){ if (true) { new Aedu.ResearchInterestListCard({ el: $('*[data-has-card-for-ri-list=65625325]'), work: {"id":65625325,"title":"Programming languages in economics","created_at":"2021-12-22T23:46:47.419-08:00","url":"https://www.academia.edu/65625325/Programming_languages_in_economics?f_ri=725","dom_id":"work_65625325","summary":"Young economists sometimes ask which computer programming languages they should learn. This paper answers that question by suggesting that they begin with a high level language like GAUSS, GAMS, Mathematica, Maple or MATLAB depending on their field of specialization in economics. Then they should work down to one of the low level languages such as Fortran, Basic, C, C++ or Java depending on the planned areas of application. Finally, they should proceed to the languages which are used to develop graphical interfaces and internet applications, viz. Visual Basic,","downloadable_attachments":[{"id":77140592,"asset_id":65625325,"asset_type":"Work","always_allow_download":false}],"ordered_authors":[{"id":154963618,"first_name":"Hans","last_name":"Amman","domain_name":"independent","page_name":"HansAmman","display_name":"Hans Amman","profile_url":"https://independent.academia.edu/HansAmman?f_ri=725","photo":"/images/s65_no_pic.png"}],"research_interests":[{"id":451,"name":"Programming Languages","url":"https://www.academia.edu/Documents/in/Programming_Languages?f_ri=725","nofollow":true},{"id":724,"name":"Economics","url":"https://www.academia.edu/Documents/in/Economics?f_ri=725","nofollow":true},{"id":725,"name":"Computational Economics","url":"https://www.academia.edu/Documents/in/Computational_Economics?f_ri=725","nofollow":true},{"id":747,"name":"Econometrics","url":"https://www.academia.edu/Documents/in/Econometrics?f_ri=725","nofollow":true},{"id":47820,"name":"Visual basic","url":"https://www.academia.edu/Documents/in/Visual_basic?f_ri=725"},{"id":70448,"name":"Fortran","url":"https://www.academia.edu/Documents/in/Fortran?f_ri=725"},{"id":98569,"name":"Computer Languages","url":"https://www.academia.edu/Documents/in/Computer_Languages?f_ri=725"},{"id":258979,"name":"Computer Program","url":"https://www.academia.edu/Documents/in/Computer_Program?f_ri=725"},{"id":384624,"name":"Rich Internet Application","url":"https://www.academia.edu/Documents/in/Rich_Internet_Application?f_ri=725"},{"id":1329323,"name":"Graphical User Interface","url":"https://www.academia.edu/Documents/in/Graphical_User_Interface?f_ri=725"},{"id":1489478,"name":"Programming language","url":"https://www.academia.edu/Documents/in/Programming_language?f_ri=725"},{"id":3079415,"name":"Finance and Investment Banking","url":"https://www.academia.edu/Documents/in/Finance_and_Investment_Banking?f_ri=725"}]}, }) } })();</script></ul></li></ul></div></div><div class="u-borderBottom1 u-borderColorGrayLighter"><div class="clearfix u-pv7x u-mb0x js-work-card work_16662268 coauthored" data-work_id="16662268" itemscope="itemscope" itemtype="https://schema.org/ScholarlyArticle"><div class="header"><div class="title u-fontSerif u-fs22 u-lineHeight1_3"><a class="u-tcGrayDarkest js-work-link" href="https://www.academia.edu/16662268/Equilibrium_in_a_Dynamic_Limit_Order_Market">Equilibrium in a Dynamic Limit Order Market</a></div></div><div class="u-pb4x u-mt3x"><div class="summary u-fs14 u-fw300 u-lineHeight1_5 u-tcGrayDarkest"><div class="summarized">We model a dynamic limit order market as a stochastic sequential game. Since the model is analytically intractable, we provide an algorithm based on to find a stationary Markov-perfect equilibrium. Given the stationary equilibrium, we... <a class="more_link u-tcGrayDark u-linkUnstyled" data-container=".work_16662268" data-show=".complete" data-hide=".summarized" data-more-link-behavior="true" href="#">more</a></div><div class="complete hidden">We model a dynamic limit order market as a stochastic sequential game. Since the model is analytically intractable, we provide an algorithm based on to find a stationary Markov-perfect equilibrium. Given the stationary equilibrium, we generate artificial time series and perform comparative dynamics. We demonstrate that the order flow displays persistence. As we know the data generating process, we can compare transaction prices to the true value of the asset, as well as explicitly determine the welfare gains accruing to investors. Due to the endogeneity of order flow, the midpoint of the quoted prices is not a good proxy for the true value. Further, transaction costs paid by market order submitters are negative on average. The effective spread is negatively correlated with true transaction costs, and largely uncorrelated with changes in investor surplus. As a policy experiment, we consider the effect of a change in tick size, and find that it has a very small positive impact on investor surplus.</div></div></div><ul class="InlineList u-ph0x u-fs13"><li class="InlineList-item logged_in_only"><div class="share_on_academia_work_button"><a class="academia_share Button Button--inverseBlue Button--sm js-bookmark-button" data-academia-share="Work/16662268" data-share-source="work_strip" data-spinner="small_white_hide_contents"><i class="fa fa-plus"></i><span class="work-strip-link-text u-ml1x" data-content="button_text">Bookmark</span></a></div></li><li class="InlineList-item"><div class="download"><a id="f04a00e9731ee4d74305e67587c8e7fe" rel="nofollow" data-download="{"attachment_id":39106033,"asset_id":16662268,"asset_type":"Work","always_allow_download":false,"track":null,"button_location":"work_strip","source":null,"hide_modal":null}" class="Button Button--sm Button--inverseGreen js-download-button prompt_button doc_download" href="https://www.academia.edu/attachments/39106033/download_file?st=MTc0MDU1NDU5OSw4LjIyMi4yMDguMTQ2&s=work_strip"><i class="fa fa-arrow-circle-o-down fa-lg"></i><span class="u-textUppercase u-ml1x" data-content="button_text">Download</span></a></div></li><li class="InlineList-item"><ul class="InlineList InlineList--bordered u-ph0x"><li class="InlineList-item InlineList-item--bordered"><span class="InlineList-item-text">by <span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a class="u-tcGrayDark u-fw700" data-has-card-for-user="36024155" href="https://independent.academia.edu/ChristineParlour">Christine Parlour</a><script data-card-contents-for-user="36024155" type="text/json">{"id":36024155,"first_name":"Christine","last_name":"Parlour","domain_name":"independent","page_name":"ChristineParlour","display_name":"Christine Parlour","profile_url":"https://independent.academia.edu/ChristineParlour?f_ri=725","photo":"/images/s65_no_pic.png"}</script></span></span><span class="u-displayInlineBlock InlineList-item-text"> and <span class="u-textDecorationUnderline u-clickable InlineList-item-text js-work-more-authors-16662268">+1</span><div class="hidden js-additional-users-16662268"><div><span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a href="https://rochester.academia.edu/RonaldGoettler">Ronald Goettler</a></span></div></div></span><script>(function(){ var popoverSettings = { el: $('.js-work-more-authors-16662268'), placement: 'bottom', hide_delay: 200, html: true, content: function(){ return $('.js-additional-users-16662268').html(); 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Since the model is analytically intractable, we provide an algorithm based on to find a stationary Markov-perfect equilibrium. Given the stationary equilibrium, we generate artificial time series and perform comparative dynamics. We demonstrate that the order flow displays persistence. As we know the data generating process, we can compare transaction prices to the true value of the asset, as well as explicitly determine the welfare gains accruing to investors. Due to the endogeneity of order flow, the midpoint of the quoted prices is not a good proxy for the true value. Further, transaction costs paid by market order submitters are negative on average. The effective spread is negatively correlated with true transaction costs, and largely uncorrelated with changes in investor surplus. As a policy experiment, we consider the effect of a change in tick size, and find that it has a very small positive impact on investor surplus.","downloadable_attachments":[{"id":39106033,"asset_id":16662268,"asset_type":"Work","always_allow_download":false}],"ordered_authors":[{"id":36024155,"first_name":"Christine","last_name":"Parlour","domain_name":"independent","page_name":"ChristineParlour","display_name":"Christine Parlour","profile_url":"https://independent.academia.edu/ChristineParlour?f_ri=725","photo":"/images/s65_no_pic.png"},{"id":36098322,"first_name":"Ronald","last_name":"Goettler","domain_name":"rochester","page_name":"RonaldGoettler","display_name":"Ronald Goettler","profile_url":"https://rochester.academia.edu/RonaldGoettler?f_ri=725","photo":"/images/s65_no_pic.png"}],"research_interests":[{"id":47,"name":"Finance","url":"https://www.academia.edu/Documents/in/Finance?f_ri=725","nofollow":true},{"id":725,"name":"Computational Economics","url":"https://www.academia.edu/Documents/in/Computational_Economics?f_ri=725","nofollow":true},{"id":4456,"name":"Time Series","url":"https://www.academia.edu/Documents/in/Time_Series?f_ri=725","nofollow":true},{"id":270673,"name":"Financial Market","url":"https://www.academia.edu/Documents/in/Financial_Market?f_ri=725","nofollow":true},{"id":868794,"name":"Transaction Cost","url":"https://www.academia.edu/Documents/in/Transaction_Cost?f_ri=725"}]}, }) } })();</script></ul></li></ul></div></div><div class="u-borderBottom1 u-borderColorGrayLighter"><div class="clearfix u-pv7x u-mb0x js-work-card work_30336286" data-work_id="30336286" itemscope="itemscope" itemtype="https://schema.org/ScholarlyArticle"><div class="header"><div class="title u-fontSerif u-fs22 u-lineHeight1_3"><a class="u-tcGrayDarkest js-work-link" href="https://www.academia.edu/30336286/Programming_languages_in_economics">Programming languages in economics</a></div></div><div class="u-pb4x u-mt3x"><div class="summary u-fs14 u-fw300 u-lineHeight1_5 u-tcGrayDarkest"><div class="summarized">Young economists sometimes ask which computer programming languages they should learn. This paper answers that question by suggesting that they begin with a high level language like GAUSS, GAMS, Mathematica, Maple or MATLAB depending on... <a class="more_link u-tcGrayDark u-linkUnstyled" data-container=".work_30336286" data-show=".complete" data-hide=".summarized" data-more-link-behavior="true" href="#">more</a></div><div class="complete hidden">Young economists sometimes ask which computer programming languages they should learn. This paper answers that question by suggesting that they begin with a high level language like GAUSS, GAMS, Mathematica, Maple or MATLAB depending on their field of specialization in economics. Then they should work down to one of the low level languages such as Fortran, Basic, C, C++ or Java depending on the planned areas of application. Finally, they should proceed to the languages which are used to develop graphical interfaces and internet applications, viz. Visual Basic, C, C++ or Java.</div></div></div><ul class="InlineList u-ph0x u-fs13"><li class="InlineList-item logged_in_only"><div class="share_on_academia_work_button"><a class="academia_share Button Button--inverseBlue Button--sm js-bookmark-button" data-academia-share="Work/30336286" data-share-source="work_strip" data-spinner="small_white_hide_contents"><i class="fa fa-plus"></i><span class="work-strip-link-text u-ml1x" data-content="button_text">Bookmark</span></a></div></li><li class="InlineList-item"><div class="download"><a id="a6a023502c24e83d535db0191e9e6b3d" rel="nofollow" data-download="{"attachment_id":50789873,"asset_id":30336286,"asset_type":"Work","always_allow_download":false,"track":null,"button_location":"work_strip","source":null,"hide_modal":null}" class="Button Button--sm Button--inverseGreen js-download-button prompt_button doc_download" href="https://www.academia.edu/attachments/50789873/download_file?st=MTc0MDU1NDU5OSw4LjIyMi4yMDguMTQ2&s=work_strip"><i class="fa fa-arrow-circle-o-down fa-lg"></i><span class="u-textUppercase u-ml1x" data-content="button_text">Download</span></a></div></li><li class="InlineList-item"><ul class="InlineList InlineList--bordered u-ph0x"><li class="InlineList-item InlineList-item--bordered"><span class="InlineList-item-text">by <span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a class="u-tcGrayDark u-fw700" data-has-card-for-user="57824411" href="https://independent.academia.edu/DavidKendrick3">David Kendrick</a><script data-card-contents-for-user="57824411" type="text/json">{"id":57824411,"first_name":"David","last_name":"Kendrick","domain_name":"independent","page_name":"DavidKendrick3","display_name":"David Kendrick","profile_url":"https://independent.academia.edu/DavidKendrick3?f_ri=725","photo":"/images/s65_no_pic.png"}</script></span></span></li><li class="js-paper-rank-work_30336286 InlineList-item InlineList-item--bordered hidden"><span class="js-paper-rank-view hidden u-tcGrayDark" data-paper-rank-work-id="30336286"><i class="u-m1x fa fa-bar-chart"></i><strong class="js-paper-rank"></strong></span><script>$(function() { new Works.PaperRankView({ workId: 30336286, container: ".js-paper-rank-work_30336286", }); 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$(".js-view-count[data-work-id=30336286]").text(description); $(".js-view-count-work_30336286").attr('title', description).tooltip(); }); });</script></span><script>$(function() { $(".js-view-count-work_30336286").removeClass('hidden') })</script></div></li><li class="InlineList-item u-positionRelative" style="max-width: 250px"><div class="u-positionAbsolute" data-has-card-for-ri-list="30336286"><i class="fa fa-tag InlineList-item-icon u-positionRelative"></i>  <a class="InlineList-item-text u-positionRelative">9</a>  </div><span class="InlineList-item-text u-textTruncate u-pl9x"><a class="InlineList-item-text" data-has-card-for-ri="451" rel="nofollow" href="https://www.academia.edu/Documents/in/Programming_Languages">Programming Languages</a>, <script data-card-contents-for-ri="451" type="text/json">{"id":451,"name":"Programming Languages","url":"https://www.academia.edu/Documents/in/Programming_Languages?f_ri=725","nofollow":true}</script><a class="InlineList-item-text" data-has-card-for-ri="725" rel="nofollow" href="https://www.academia.edu/Documents/in/Computational_Economics">Computational Economics</a>, <script data-card-contents-for-ri="725" type="text/json">{"id":725,"name":"Computational Economics","url":"https://www.academia.edu/Documents/in/Computational_Economics?f_ri=725","nofollow":true}</script><a class="InlineList-item-text" data-has-card-for-ri="747" rel="nofollow" href="https://www.academia.edu/Documents/in/Econometrics">Econometrics</a>, <script data-card-contents-for-ri="747" type="text/json">{"id":747,"name":"Econometrics","url":"https://www.academia.edu/Documents/in/Econometrics?f_ri=725","nofollow":true}</script><a class="InlineList-item-text" data-has-card-for-ri="47820" rel="nofollow" href="https://www.academia.edu/Documents/in/Visual_basic">Visual basic</a><script data-card-contents-for-ri="47820" type="text/json">{"id":47820,"name":"Visual basic","url":"https://www.academia.edu/Documents/in/Visual_basic?f_ri=725","nofollow":true}</script></span></li><script>(function(){ if (true) { new Aedu.ResearchInterestListCard({ el: $('*[data-has-card-for-ri-list=30336286]'), work: {"id":30336286,"title":"Programming languages in economics","created_at":"2016-12-08T12:26:10.701-08:00","url":"https://www.academia.edu/30336286/Programming_languages_in_economics?f_ri=725","dom_id":"work_30336286","summary":"Young economists sometimes ask which computer programming languages they should learn. This paper answers that question by suggesting that they begin with a high level language like GAUSS, GAMS, Mathematica, Maple or MATLAB depending on their field of specialization in economics. Then they should work down to one of the low level languages such as Fortran, Basic, C, C++ or Java depending on the planned areas of application. Finally, they should proceed to the languages which are used to develop graphical interfaces and internet applications, viz. Visual Basic, C, C++ or Java.","downloadable_attachments":[{"id":50789873,"asset_id":30336286,"asset_type":"Work","always_allow_download":false}],"ordered_authors":[{"id":57824411,"first_name":"David","last_name":"Kendrick","domain_name":"independent","page_name":"DavidKendrick3","display_name":"David Kendrick","profile_url":"https://independent.academia.edu/DavidKendrick3?f_ri=725","photo":"/images/s65_no_pic.png"}],"research_interests":[{"id":451,"name":"Programming Languages","url":"https://www.academia.edu/Documents/in/Programming_Languages?f_ri=725","nofollow":true},{"id":725,"name":"Computational Economics","url":"https://www.academia.edu/Documents/in/Computational_Economics?f_ri=725","nofollow":true},{"id":747,"name":"Econometrics","url":"https://www.academia.edu/Documents/in/Econometrics?f_ri=725","nofollow":true},{"id":47820,"name":"Visual basic","url":"https://www.academia.edu/Documents/in/Visual_basic?f_ri=725","nofollow":true},{"id":70448,"name":"Fortran","url":"https://www.academia.edu/Documents/in/Fortran?f_ri=725"},{"id":98569,"name":"Computer Languages","url":"https://www.academia.edu/Documents/in/Computer_Languages?f_ri=725"},{"id":258979,"name":"Computer Program","url":"https://www.academia.edu/Documents/in/Computer_Program?f_ri=725"},{"id":384624,"name":"Rich Internet Application","url":"https://www.academia.edu/Documents/in/Rich_Internet_Application?f_ri=725"},{"id":1489478,"name":"Programming language","url":"https://www.academia.edu/Documents/in/Programming_language?f_ri=725"}]}, }) } })();</script></ul></li></ul></div></div><div class="u-borderBottom1 u-borderColorGrayLighter"><div class="clearfix u-pv7x u-mb0x js-work-card work_14950280" data-work_id="14950280" itemscope="itemscope" itemtype="https://schema.org/ScholarlyArticle"><div class="header"><div class="title u-fontSerif u-fs22 u-lineHeight1_3"><a class="u-tcGrayDarkest js-work-link" href="https://www.academia.edu/14950280/Valuing_credit_default_swap_in_a_non_homogeneous_semi_Markovian_rating_based_model">Valuing credit default swap in a non-homogeneous semi-Markovian rating based model</a></div></div><div class="u-pb4x u-mt3x"><div class="summary u-fs14 u-fw300 u-lineHeight1_5 u-tcGrayDarkest"><div class="summarized">In this paper we use a discrete time non-homogeneous semi-Markov model for the rating evolution of the credit quality of a firm C and we determine the credit default swap spread for a contract between two parties, A and B that,... <a class="more_link u-tcGrayDark u-linkUnstyled" data-container=".work_14950280" data-show=".complete" data-hide=".summarized" data-more-link-behavior="true" href="#">more</a></div><div class="complete hidden">In this paper we use a discrete time non-homogeneous semi-Markov model for the rating evolution of the credit quality of a firm C and we determine the credit default swap spread for a contract between two parties, A and B that, respectively, sell and buy a protection about the failure of the firm C. We work in both the case of deterministic and stochastic recovery rate. We highlight the link between credit risk and reliability theory too.</div></div></div><ul class="InlineList u-ph0x u-fs13"><li class="InlineList-item logged_in_only"><div class="share_on_academia_work_button"><a class="academia_share Button Button--inverseBlue Button--sm js-bookmark-button" data-academia-share="Work/14950280" data-share-source="work_strip" data-spinner="small_white_hide_contents"><i class="fa fa-plus"></i><span class="work-strip-link-text u-ml1x" data-content="button_text">Bookmark</span></a></div></li><li class="InlineList-item"><div class="download"><a id="454a157b2d4c5461f851b98dd2b5e2b0" rel="nofollow" data-download="{"attachment_id":43709562,"asset_id":14950280,"asset_type":"Work","always_allow_download":false,"track":null,"button_location":"work_strip","source":null,"hide_modal":null}" class="Button Button--sm Button--inverseGreen js-download-button prompt_button doc_download" href="https://www.academia.edu/attachments/43709562/download_file?st=MTc0MDU1NDU5OSw4LjIyMi4yMDguMTQ2&s=work_strip"><i class="fa fa-arrow-circle-o-down fa-lg"></i><span class="u-textUppercase u-ml1x" data-content="button_text">Download</span></a></div></li><li class="InlineList-item"><ul class="InlineList InlineList--bordered u-ph0x"><li class="InlineList-item InlineList-item--bordered"><span class="InlineList-item-text">by <span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a class="u-tcGrayDark u-fw700" data-has-card-for-user="33944075" href="https://uniroma1.academia.edu/RaimondoManca">Raimondo Manca</a><script data-card-contents-for-user="33944075" type="text/json">{"id":33944075,"first_name":"Raimondo","last_name":"Manca","domain_name":"uniroma1","page_name":"RaimondoManca","display_name":"Raimondo Manca","profile_url":"https://uniroma1.academia.edu/RaimondoManca?f_ri=725","photo":"/images/s65_no_pic.png"}</script></span></span></li><li class="js-paper-rank-work_14950280 InlineList-item InlineList-item--bordered hidden"><span class="js-paper-rank-view hidden u-tcGrayDark" data-paper-rank-work-id="14950280"><i class="u-m1x fa fa-bar-chart"></i><strong class="js-paper-rank"></strong></span><script>$(function() { new Works.PaperRankView({ workId: 14950280, container: ".js-paper-rank-work_14950280", }); 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$(".js-view-count[data-work-id=14950280]").text(description); $(".js-view-count-work_14950280").attr('title', description).tooltip(); }); });</script></span><script>$(function() { $(".js-view-count-work_14950280").removeClass('hidden') })</script></div></li><li class="InlineList-item u-positionRelative" style="max-width: 250px"><div class="u-positionAbsolute" data-has-card-for-ri-list="14950280"><i class="fa fa-tag InlineList-item-icon u-positionRelative"></i>  <a class="InlineList-item-text u-positionRelative">5</a>  </div><span class="InlineList-item-text u-textTruncate u-pl9x"><a class="InlineList-item-text" data-has-card-for-ri="725" rel="nofollow" href="https://www.academia.edu/Documents/in/Computational_Economics">Computational Economics</a>, <script data-card-contents-for-ri="725" type="text/json">{"id":725,"name":"Computational Economics","url":"https://www.academia.edu/Documents/in/Computational_Economics?f_ri=725","nofollow":true}</script><a class="InlineList-item-text" data-has-card-for-ri="747" rel="nofollow" href="https://www.academia.edu/Documents/in/Econometrics">Econometrics</a>, <script data-card-contents-for-ri="747" type="text/json">{"id":747,"name":"Econometrics","url":"https://www.academia.edu/Documents/in/Econometrics?f_ri=725","nofollow":true}</script><a class="InlineList-item-text" data-has-card-for-ri="85998" rel="nofollow" href="https://www.academia.edu/Documents/in/Credit_Risk">Credit Risk</a>, <script data-card-contents-for-ri="85998" type="text/json">{"id":85998,"name":"Credit Risk","url":"https://www.academia.edu/Documents/in/Credit_Risk?f_ri=725","nofollow":true}</script><a class="InlineList-item-text" data-has-card-for-ri="991101" rel="nofollow" href="https://www.academia.edu/Documents/in/Discrete_Time_Systems">Discrete Time Systems</a><script data-card-contents-for-ri="991101" type="text/json">{"id":991101,"name":"Discrete Time Systems","url":"https://www.academia.edu/Documents/in/Discrete_Time_Systems?f_ri=725","nofollow":true}</script></span></li><script>(function(){ if (true) { new Aedu.ResearchInterestListCard({ el: $('*[data-has-card-for-ri-list=14950280]'), work: {"id":14950280,"title":"Valuing credit default swap in a non-homogeneous semi-Markovian rating based model","created_at":"2015-08-15T23:40:52.136-07:00","url":"https://www.academia.edu/14950280/Valuing_credit_default_swap_in_a_non_homogeneous_semi_Markovian_rating_based_model?f_ri=725","dom_id":"work_14950280","summary":"In this paper we use a discrete time non-homogeneous semi-Markov model for the rating evolution of the credit quality of a firm C and we determine the credit default swap spread for a contract between two parties, A and B that, respectively, sell and buy a protection about the failure of the firm C. We work in both the case of deterministic and stochastic recovery rate. We highlight the link between credit risk and reliability theory too.","downloadable_attachments":[{"id":43709562,"asset_id":14950280,"asset_type":"Work","always_allow_download":false}],"ordered_authors":[{"id":33944075,"first_name":"Raimondo","last_name":"Manca","domain_name":"uniroma1","page_name":"RaimondoManca","display_name":"Raimondo Manca","profile_url":"https://uniroma1.academia.edu/RaimondoManca?f_ri=725","photo":"/images/s65_no_pic.png"}],"research_interests":[{"id":725,"name":"Computational Economics","url":"https://www.academia.edu/Documents/in/Computational_Economics?f_ri=725","nofollow":true},{"id":747,"name":"Econometrics","url":"https://www.academia.edu/Documents/in/Econometrics?f_ri=725","nofollow":true},{"id":85998,"name":"Credit Risk","url":"https://www.academia.edu/Documents/in/Credit_Risk?f_ri=725","nofollow":true},{"id":991101,"name":"Discrete Time Systems","url":"https://www.academia.edu/Documents/in/Discrete_Time_Systems?f_ri=725","nofollow":true},{"id":2050770,"name":"Markov model","url":"https://www.academia.edu/Documents/in/Markov_model?f_ri=725"}]}, }) } })();</script></ul></li></ul></div></div><div class="u-borderBottom1 u-borderColorGrayLighter"><div class="clearfix u-pv7x u-mb0x js-work-card work_34427750" data-work_id="34427750" itemscope="itemscope" itemtype="https://schema.org/ScholarlyArticle"><div class="header"><div class="title u-fontSerif u-fs22 u-lineHeight1_3"><a class="u-tcGrayDarkest js-work-link" href="https://www.academia.edu/34427750/A_Genetic_Programming_Approach_for_EUR_USD_Exchange_Rate_Forecasting_and_Trading">A Genetic Programming Approach for EUR/USD Exchange Rate Forecasting and Trading</a></div></div><div class="u-pb4x u-mt3x"><div class="summary u-fs14 u-fw300 u-lineHeight1_5 u-tcGrayDarkest"><div class="summarized">The purpose of this article is to present a novel genetic programming trading technique in the task of forecasting the next day returns when trading the EUR/USD exchange rate based on the exchange rates of historical data. Aiming at... <a class="more_link u-tcGrayDark u-linkUnstyled" data-container=".work_34427750" data-show=".complete" data-hide=".summarized" data-more-link-behavior="true" href="#">more</a></div><div class="complete hidden">The purpose of this article is to present a novel genetic programming trading technique in the task of forecasting the next day returns when trading the EUR/USD exchange rate based on the exchange rates of historical data. Aiming at testing its effectiveness, we benchmark the forecasting performance of our genetic programming implementation with three traditional strategies (naive strategy, MACD, and a buy & hold strategy) plus a hybrid evolutionary artificial neural network approach. The proposed genetic programming technique was found to demonstrate the highest trading performance in terms of annualized return and information ratio when compared to all other strategies which have been used. When more elaborate trading techniques, such as leverage, were combined with the examined models, the genetic programming approach still presented the highest trading performance. To the best</div></div></div><ul class="InlineList u-ph0x u-fs13"><li class="InlineList-item logged_in_only"><div class="share_on_academia_work_button"><a class="academia_share Button Button--inverseBlue Button--sm js-bookmark-button" data-academia-share="Work/34427750" data-share-source="work_strip" data-spinner="small_white_hide_contents"><i class="fa fa-plus"></i><span class="work-strip-link-text u-ml1x" data-content="button_text">Bookmark</span></a></div></li><li class="InlineList-item"><div class="download"><a id="3947fda7f40620c77342264bafa85ed8" rel="nofollow" data-download="{"attachment_id":54304325,"asset_id":34427750,"asset_type":"Work","always_allow_download":false,"track":null,"button_location":"work_strip","source":null,"hide_modal":null}" class="Button Button--sm Button--inverseGreen js-download-button prompt_button doc_download" href="https://www.academia.edu/attachments/54304325/download_file?st=MTc0MDU1NDU5OSw4LjIyMi4yMDguMTQ2&s=work_strip"><i class="fa fa-arrow-circle-o-down fa-lg"></i><span class="u-textUppercase u-ml1x" data-content="button_text">Download</span></a></div></li><li class="InlineList-item"><ul class="InlineList InlineList--bordered u-ph0x"><li class="InlineList-item InlineList-item--bordered"><span class="InlineList-item-text">by <span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a class="u-tcGrayDark u-fw700" data-has-card-for-user="118740" href="https://upatras.academia.edu/SpirosLikothanassis">Spiros Likothanassis</a><script data-card-contents-for-user="118740" type="text/json">{"id":118740,"first_name":"Spiros","last_name":"Likothanassis","domain_name":"upatras","page_name":"SpirosLikothanassis","display_name":"Spiros Likothanassis","profile_url":"https://upatras.academia.edu/SpirosLikothanassis?f_ri=725","photo":"https://0.academia-photos.com/118740/18295483/18263986/s65_spiros.likothanassis.jpg"}</script></span></span></li><li class="js-paper-rank-work_34427750 InlineList-item InlineList-item--bordered hidden"><span class="js-paper-rank-view hidden u-tcGrayDark" data-paper-rank-work-id="34427750"><i class="u-m1x fa fa-bar-chart"></i><strong class="js-paper-rank"></strong></span><script>$(function() { new Works.PaperRankView({ workId: 34427750, container: ".js-paper-rank-work_34427750", }); 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Aiming at testing its effectiveness, we benchmark the forecasting performance of our genetic programming implementation with three traditional strategies (naive strategy, MACD, and a buy \u0026 hold strategy) plus a hybrid evolutionary artificial neural network approach. The proposed genetic programming technique was found to demonstrate the highest trading performance in terms of annualized return and information ratio when compared to all other strategies which have been used. When more elaborate trading techniques, such as leverage, were combined with the examined models, the genetic programming approach still presented the highest trading performance. To the best","downloadable_attachments":[{"id":54304325,"asset_id":34427750,"asset_type":"Work","always_allow_download":false}],"ordered_authors":[{"id":118740,"first_name":"Spiros","last_name":"Likothanassis","domain_name":"upatras","page_name":"SpirosLikothanassis","display_name":"Spiros Likothanassis","profile_url":"https://upatras.academia.edu/SpirosLikothanassis?f_ri=725","photo":"https://0.academia-photos.com/118740/18295483/18263986/s65_spiros.likothanassis.jpg"}],"research_interests":[{"id":725,"name":"Computational Economics","url":"https://www.academia.edu/Documents/in/Computational_Economics?f_ri=725","nofollow":true},{"id":747,"name":"Econometrics","url":"https://www.academia.edu/Documents/in/Econometrics?f_ri=725","nofollow":true},{"id":1701,"name":"Evolutionary algorithms","url":"https://www.academia.edu/Documents/in/Evolutionary_algorithms?f_ri=725","nofollow":true},{"id":5025,"name":"Genetic Programming","url":"https://www.academia.edu/Documents/in/Genetic_Programming?f_ri=725","nofollow":true}]}, }) } })();</script></ul></li></ul></div></div><div class="u-borderBottom1 u-borderColorGrayLighter"><div class="clearfix u-pv7x u-mb0x js-work-card work_33459601" data-work_id="33459601" itemscope="itemscope" itemtype="https://schema.org/ScholarlyArticle"><div class="header"><div class="title u-fontSerif u-fs22 u-lineHeight1_3"><a class="u-tcGrayDarkest js-work-link" href="https://www.academia.edu/33459601/Bubbles_and_market_crashes">Bubbles and market crashes</a></div></div><div class="u-pb4x u-mt3x"><div class="summary u-fs14 u-fw300 u-lineHeight1_5 u-tcGrayDarkest"><div class="summarized">We present a dynamical theory of asset price bubbles that exhibits the appearance of bubbles and their subsequent crashes. We show that when speculative trends dominate over fundamental beliefs, bubbles form, leading to the growth of... <a class="more_link u-tcGrayDark u-linkUnstyled" data-container=".work_33459601" data-show=".complete" data-hide=".summarized" data-more-link-behavior="true" href="#">more</a></div><div class="complete hidden">We present a dynamical theory of asset price bubbles that exhibits the appearance of bubbles and their subsequent crashes. We show that when speculative trends dominate over fundamental beliefs, bubbles form, leading to the growth of asset prices away from their fundamental value. This growth makes the system increasingly susceptible to any exogenous shock, thus eventually precipitating a crash. We also present computer experiments which in their aggregate behavior confirm the predictions of the theory.</div></div></div><ul class="InlineList u-ph0x u-fs13"><li class="InlineList-item logged_in_only"><div class="share_on_academia_work_button"><a class="academia_share Button Button--inverseBlue Button--sm js-bookmark-button" data-academia-share="Work/33459601" data-share-source="work_strip" data-spinner="small_white_hide_contents"><i class="fa fa-plus"></i><span class="work-strip-link-text u-ml1x" data-content="button_text">Bookmark</span></a></div></li><li class="InlineList-item"><div class="download"><a id="a3bcb1cd51d7abab87390fd54e8a8b1a" rel="nofollow" data-download="{"attachment_id":53506166,"asset_id":33459601,"asset_type":"Work","always_allow_download":false,"track":null,"button_location":"work_strip","source":null,"hide_modal":null}" class="Button Button--sm Button--inverseGreen js-download-button prompt_button doc_download" href="https://www.academia.edu/attachments/53506166/download_file?st=MTc0MDU1NDU5OSw4LjIyMi4yMDguMTQ2&s=work_strip"><i class="fa fa-arrow-circle-o-down fa-lg"></i><span class="u-textUppercase u-ml1x" data-content="button_text">Download</span></a></div></li><li class="InlineList-item"><ul class="InlineList InlineList--bordered u-ph0x"><li class="InlineList-item InlineList-item--bordered"><span class="InlineList-item-text">by <span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a class="u-tcGrayDark u-fw700" data-has-card-for-user="42346674" href="https://independent.academia.edu/BHuberman">Bernardo Huberman</a><script data-card-contents-for-user="42346674" type="text/json">{"id":42346674,"first_name":"Bernardo","last_name":"Huberman","domain_name":"independent","page_name":"BHuberman","display_name":"Bernardo Huberman","profile_url":"https://independent.academia.edu/BHuberman?f_ri=725","photo":"/images/s65_no_pic.png"}</script></span></span></li><li class="js-paper-rank-work_33459601 InlineList-item InlineList-item--bordered hidden"><span class="js-paper-rank-view hidden u-tcGrayDark" data-paper-rank-work-id="33459601"><i class="u-m1x fa fa-bar-chart"></i><strong class="js-paper-rank"></strong></span><script>$(function() { new Works.PaperRankView({ workId: 33459601, container: ".js-paper-rank-work_33459601", }); 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We show that when speculative trends dominate over fundamental beliefs, bubbles form, leading to the growth of asset prices away from their fundamental value. This growth makes the system increasingly susceptible to any exogenous shock, thus eventually precipitating a crash. We also present computer experiments which in their aggregate behavior confirm the predictions of the theory.","downloadable_attachments":[{"id":53506166,"asset_id":33459601,"asset_type":"Work","always_allow_download":false}],"ordered_authors":[{"id":42346674,"first_name":"Bernardo","last_name":"Huberman","domain_name":"independent","page_name":"BHuberman","display_name":"Bernardo Huberman","profile_url":"https://independent.academia.edu/BHuberman?f_ri=725","photo":"/images/s65_no_pic.png"}],"research_interests":[{"id":725,"name":"Computational Economics","url":"https://www.academia.edu/Documents/in/Computational_Economics?f_ri=725","nofollow":true},{"id":747,"name":"Econometrics","url":"https://www.academia.edu/Documents/in/Econometrics?f_ri=725","nofollow":true}]}, }) } })();</script></ul></li></ul></div></div><div class="u-borderBottom1 u-borderColorGrayLighter"><div class="clearfix u-pv7x u-mb0x js-work-card work_31392025" data-work_id="31392025" itemscope="itemscope" itemtype="https://schema.org/ScholarlyArticle"><div class="header"><div class="title u-fontSerif u-fs22 u-lineHeight1_3"><a class="u-tcGrayDarkest js-work-link" href="https://www.academia.edu/31392025/The_Promises_and_Perils_of_Agent_Based_Computational_Economics_LABORatorio_Revelli_Working_Paper_No">The Promises and Perils of Agent-Based Computational Economics”, LABORatorio Revelli Working Paper No</a></div></div><div class="u-pb4x u-mt3x"><div class="summary u-fs14 u-fw300 u-lineHeight1_5 u-tcGrayDarkest"><div class="summarized">In this paper I review the main strengths and weaknesses of agent-based computational models. In particular I rationalise the main theoretical critiques, which point to the following problematic areas: (i) interpretation of the simulation... <a class="more_link u-tcGrayDark u-linkUnstyled" data-container=".work_31392025" data-show=".complete" data-hide=".summarized" data-more-link-behavior="true" href="#">more</a></div><div class="complete hidden">In this paper I review the main strengths and weaknesses of agent-based computational models. In particular I rationalise the main theoretical critiques, which point to the following problematic areas: (i) interpretation of the simulation dynamics, (ii) estimation of the simulation model, and (iii) generalisation of the results. I show that there exist solutions for all these issues. Moreover, this paper clarifies some confounding differences in terminology between the computer science and the economic literature.</div></div></div><ul class="InlineList u-ph0x u-fs13"><li class="InlineList-item logged_in_only"><div class="share_on_academia_work_button"><a class="academia_share Button Button--inverseBlue Button--sm js-bookmark-button" data-academia-share="Work/31392025" data-share-source="work_strip" data-spinner="small_white_hide_contents"><i class="fa fa-plus"></i><span class="work-strip-link-text u-ml1x" data-content="button_text">Bookmark</span></a></div></li><li class="InlineList-item"><div class="download"><a id="64715b557aa74f0c9a65eabcf6f017c4" rel="nofollow" data-download="{"attachment_id":51764951,"asset_id":31392025,"asset_type":"Work","always_allow_download":false,"track":null,"button_location":"work_strip","source":null,"hide_modal":null}" class="Button Button--sm Button--inverseGreen js-download-button prompt_button doc_download" href="https://www.academia.edu/attachments/51764951/download_file?st=MTc0MDU1NDU5OSw4LjIyMi4yMDguMTQ2&s=work_strip"><i class="fa fa-arrow-circle-o-down fa-lg"></i><span class="u-textUppercase u-ml1x" data-content="button_text">Download</span></a></div></li><li class="InlineList-item"><ul class="InlineList InlineList--bordered u-ph0x"><li class="InlineList-item InlineList-item--bordered"><span class="InlineList-item-text">by <span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a class="u-tcGrayDark u-fw700" data-has-card-for-user="34878632" href="https://utexas.academia.edu/mmi">mi mi</a><script data-card-contents-for-user="34878632" type="text/json">{"id":34878632,"first_name":"mi","last_name":"mi","domain_name":"utexas","page_name":"mmi","display_name":"mi mi","profile_url":"https://utexas.academia.edu/mmi?f_ri=725","photo":"https://0.academia-photos.com/34878632/143403078/160386091/s65_matteo.richiardi.jpg"}</script></span></span></li><li class="js-paper-rank-work_31392025 InlineList-item InlineList-item--bordered hidden"><span class="js-paper-rank-view hidden u-tcGrayDark" data-paper-rank-work-id="31392025"><i class="u-m1x fa fa-bar-chart"></i><strong class="js-paper-rank"></strong></span><script>$(function() { new Works.PaperRankView({ workId: 31392025, container: ".js-paper-rank-work_31392025", }); 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$(".js-view-count[data-work-id=31392025]").text(description); $(".js-view-count-work_31392025").attr('title', description).tooltip(); }); });</script></span><script>$(function() { $(".js-view-count-work_31392025").removeClass('hidden') })</script></div></li><li class="InlineList-item u-positionRelative" style="max-width: 250px"><div class="u-positionAbsolute" data-has-card-for-ri-list="31392025"><i class="fa fa-tag InlineList-item-icon u-positionRelative"></i>  <a class="InlineList-item-text u-positionRelative">4</a>  </div><span class="InlineList-item-text u-textTruncate u-pl9x"><a class="InlineList-item-text" data-has-card-for-ri="725" rel="nofollow" href="https://www.academia.edu/Documents/in/Computational_Economics">Computational Economics</a>, <script data-card-contents-for-ri="725" type="text/json">{"id":725,"name":"Computational Economics","url":"https://www.academia.edu/Documents/in/Computational_Economics?f_ri=725","nofollow":true}</script><a class="InlineList-item-text" data-has-card-for-ri="5337" rel="nofollow" href="https://www.academia.edu/Documents/in/Agent_Based_Simulation">Agent Based Simulation</a>, <script data-card-contents-for-ri="5337" type="text/json">{"id":5337,"name":"Agent Based Simulation","url":"https://www.academia.edu/Documents/in/Agent_Based_Simulation?f_ri=725","nofollow":true}</script><a class="InlineList-item-text" data-has-card-for-ri="85294" rel="nofollow" href="https://www.academia.edu/Documents/in/Computer_Model">Computer Model</a>, <script data-card-contents-for-ri="85294" type="text/json">{"id":85294,"name":"Computer Model","url":"https://www.academia.edu/Documents/in/Computer_Model?f_ri=725","nofollow":true}</script><a class="InlineList-item-text" data-has-card-for-ri="1208732" rel="nofollow" href="https://www.academia.edu/Documents/in/Simulation_Model">Simulation Model</a><script data-card-contents-for-ri="1208732" type="text/json">{"id":1208732,"name":"Simulation Model","url":"https://www.academia.edu/Documents/in/Simulation_Model?f_ri=725","nofollow":true}</script></span></li><script>(function(){ if (true) { new Aedu.ResearchInterestListCard({ el: $('*[data-has-card-for-ri-list=31392025]'), work: {"id":31392025,"title":"The Promises and Perils of Agent-Based Computational Economics”, LABORatorio Revelli Working Paper No","created_at":"2017-02-12T13:47:59.852-08:00","url":"https://www.academia.edu/31392025/The_Promises_and_Perils_of_Agent_Based_Computational_Economics_LABORatorio_Revelli_Working_Paper_No?f_ri=725","dom_id":"work_31392025","summary":"In this paper I review the main strengths and weaknesses of agent-based computational models. In particular I rationalise the main theoretical critiques, which point to the following problematic areas: (i) interpretation of the simulation dynamics, (ii) estimation of the simulation model, and (iii) generalisation of the results. I show that there exist solutions for all these issues. Moreover, this paper clarifies some confounding differences in terminology between the computer science and the economic literature.","downloadable_attachments":[{"id":51764951,"asset_id":31392025,"asset_type":"Work","always_allow_download":false}],"ordered_authors":[{"id":34878632,"first_name":"mi","last_name":"mi","domain_name":"utexas","page_name":"mmi","display_name":"mi mi","profile_url":"https://utexas.academia.edu/mmi?f_ri=725","photo":"https://0.academia-photos.com/34878632/143403078/160386091/s65_matteo.richiardi.jpg"}],"research_interests":[{"id":725,"name":"Computational Economics","url":"https://www.academia.edu/Documents/in/Computational_Economics?f_ri=725","nofollow":true},{"id":5337,"name":"Agent Based Simulation","url":"https://www.academia.edu/Documents/in/Agent_Based_Simulation?f_ri=725","nofollow":true},{"id":85294,"name":"Computer Model","url":"https://www.academia.edu/Documents/in/Computer_Model?f_ri=725","nofollow":true},{"id":1208732,"name":"Simulation Model","url":"https://www.academia.edu/Documents/in/Simulation_Model?f_ri=725","nofollow":true}]}, }) } })();</script></ul></li></ul></div></div><div class="u-borderBottom1 u-borderColorGrayLighter"><div class="clearfix u-pv7x u-mb0x js-work-card work_7270699 coauthored" data-work_id="7270699" itemscope="itemscope" itemtype="https://schema.org/ScholarlyArticle"><div class="header"><div class="title u-fontSerif u-fs22 u-lineHeight1_3"><a class="u-tcGrayDarkest js-work-link" href="https://www.academia.edu/7270699/Approximated_Distributions_of_Sampling_Inequality_Indices">Approximated Distributions of Sampling Inequality Indices</a></div></div><div class="u-pb4x u-mt3x"><div class="summary u-fs14 u-fw300 u-lineHeight1_5 u-tcGrayDarkest"><div class="summarized">Often, in finite samples, the true level of the confidence intervals for natural estimators of inequality indices belonging to the Gini family differs greatly from their nominal level, which is based on the asymptotic confidence limits.... <a class="more_link u-tcGrayDark u-linkUnstyled" data-container=".work_7270699" data-show=".complete" data-hide=".summarized" data-more-link-behavior="true" href="#">more</a></div><div class="complete hidden">Often, in finite samples, the true level of the confidence intervals for natural estimators of inequality indices belonging to the Gini family differs greatly from their nominal level, which is based on the asymptotic confidence limits. This paper shows how the Gram-Charlier series can be used to obtain improved finite-sample confidence intervals. Our work focuses on the implementation in Mathematica 3.0 of computational procedures to compute the Gram-Charlier distribution for the following sampling inequality indices: R by Gini, P by Piesch and M by Mehran for the Dagum (Type I) distribution. The results of a Monte Carlo experiment confirm that, for the cases investigated, the Gram-Charlier distribution largely eliminates the problem of incorrect finite-sample level.</div></div></div><ul class="InlineList u-ph0x u-fs13"><li class="InlineList-item logged_in_only"><div class="share_on_academia_work_button"><a class="academia_share Button Button--inverseBlue Button--sm js-bookmark-button" data-academia-share="Work/7270699" data-share-source="work_strip" data-spinner="small_white_hide_contents"><i class="fa fa-plus"></i><span class="work-strip-link-text u-ml1x" data-content="button_text">Bookmark</span></a></div></li><li class="InlineList-item"><div class="download"><a id="cd90be3e476e41b08bebd1eb0ffd6ab0" rel="nofollow" data-download="{"attachment_id":48543538,"asset_id":7270699,"asset_type":"Work","always_allow_download":false,"track":null,"button_location":"work_strip","source":null,"hide_modal":null}" class="Button Button--sm Button--inverseGreen js-download-button prompt_button doc_download" href="https://www.academia.edu/attachments/48543538/download_file?st=MTc0MDU1NDYwMCw4LjIyMi4yMDguMTQ2&s=work_strip"><i class="fa fa-arrow-circle-o-down fa-lg"></i><span class="u-textUppercase u-ml1x" data-content="button_text">Download</span></a></div></li><li class="InlineList-item"><ul class="InlineList InlineList--bordered u-ph0x"><li class="InlineList-item InlineList-item--bordered"><span class="InlineList-item-text">by <span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a class="u-tcGrayDark u-fw700" data-has-card-for-user="50595295" href="https://independent.academia.edu/CosimoSpera">Cosimo Spera</a><script data-card-contents-for-user="50595295" type="text/json">{"id":50595295,"first_name":"Cosimo","last_name":"Spera","domain_name":"independent","page_name":"CosimoSpera","display_name":"Cosimo Spera","profile_url":"https://independent.academia.edu/CosimoSpera?f_ri=725","photo":"/images/s65_no_pic.png"}</script></span></span><span class="u-displayInlineBlock InlineList-item-text"> and <span class="u-textDecorationUnderline u-clickable InlineList-item-text js-work-more-authors-7270699">+1</span><div class="hidden js-additional-users-7270699"><div><span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a href="https://unisi.academia.edu/paolapalmitesta">paola palmitesta</a></span></div></div></span><script>(function(){ var popoverSettings = { el: $('.js-work-more-authors-7270699'), placement: 'bottom', hide_delay: 200, html: true, content: function(){ return $('.js-additional-users-7270699').html(); 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This paper shows how the Gram-Charlier series can be used to obtain improved finite-sample confidence intervals. Our work focuses on the implementation in Mathematica 3.0 of computational procedures to compute the Gram-Charlier distribution for the following sampling inequality indices: R by Gini, P by Piesch and M by Mehran for the Dagum (Type I) distribution. The results of a Monte Carlo experiment confirm that, for the cases investigated, the Gram-Charlier distribution largely eliminates the problem of incorrect finite-sample level.","downloadable_attachments":[{"id":48543538,"asset_id":7270699,"asset_type":"Work","always_allow_download":false}],"ordered_authors":[{"id":50595295,"first_name":"Cosimo","last_name":"Spera","domain_name":"independent","page_name":"CosimoSpera","display_name":"Cosimo Spera","profile_url":"https://independent.academia.edu/CosimoSpera?f_ri=725","photo":"/images/s65_no_pic.png"},{"id":7403333,"first_name":"paola","last_name":"palmitesta","domain_name":"unisi","page_name":"paolapalmitesta","display_name":"paola palmitesta","profile_url":"https://unisi.academia.edu/paolapalmitesta?f_ri=725","photo":"https://0.academia-photos.com/7403333/80815261/69399732/s65_paola.palmitesta.jpeg"}],"research_interests":[{"id":725,"name":"Computational Economics","url":"https://www.academia.edu/Documents/in/Computational_Economics?f_ri=725","nofollow":true},{"id":747,"name":"Econometrics","url":"https://www.academia.edu/Documents/in/Econometrics?f_ri=725","nofollow":true},{"id":1228884,"name":"Confidence Limit","url":"https://www.academia.edu/Documents/in/Confidence_Limit?f_ri=725","nofollow":true},{"id":1587858,"name":"Confidence Interval","url":"https://www.academia.edu/Documents/in/Confidence_Interval?f_ri=725","nofollow":true}]}, }) } })();</script></ul></li></ul></div></div><div class="u-borderBottom1 u-borderColorGrayLighter"><div class="clearfix u-pv7x u-mb0x js-work-card work_25508105" data-work_id="25508105" itemscope="itemscope" itemtype="https://schema.org/ScholarlyArticle"><div class="header"><div class="title u-fontSerif u-fs22 u-lineHeight1_3"><a class="u-tcGrayDarkest js-work-link" href="https://www.academia.edu/25508105/Graphical_Methods_Inductive_Causal_Inference_and_Econometrics_A_Literature_Review">Graphical Methods, Inductive Causal Inference, and Econometrics: A Literature Review</a></div></div><div class="u-pb4x u-mt3x"><div class="summary u-fs14 u-fw300 u-lineHeight1_5 u-tcGrayDarkest">Recent work with graphical methods for inductive causal inference with observational econometric data is reviewed and compared with earlier work. Two alternative algorithms are described. Caveats on applications are discussed.</div></div><ul class="InlineList u-ph0x u-fs13"><li class="InlineList-item logged_in_only"><div class="share_on_academia_work_button"><a class="academia_share Button Button--inverseBlue Button--sm js-bookmark-button" data-academia-share="Work/25508105" data-share-source="work_strip" data-spinner="small_white_hide_contents"><i class="fa fa-plus"></i><span class="work-strip-link-text u-ml1x" data-content="button_text">Bookmark</span></a></div></li><li class="InlineList-item"><div class="download"><a id="b2783dd779ae088ac26ab73eed8a9b66" rel="nofollow" data-download="{"attachment_id":45829925,"asset_id":25508105,"asset_type":"Work","always_allow_download":false,"track":null,"button_location":"work_strip","source":null,"hide_modal":null}" class="Button Button--sm Button--inverseGreen js-download-button prompt_button doc_download" href="https://www.academia.edu/attachments/45829925/download_file?st=MTc0MDU1NDYwMCw4LjIyMi4yMDguMTQ2&s=work_strip"><i class="fa fa-arrow-circle-o-down fa-lg"></i><span class="u-textUppercase u-ml1x" data-content="button_text">Download</span></a></div></li><li class="InlineList-item"><ul class="InlineList InlineList--bordered u-ph0x"><li class="InlineList-item InlineList-item--bordered"><span class="InlineList-item-text">by <span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a class="u-tcGrayDark u-fw700" data-has-card-for-user="35315987" href="https://independent.academia.edu/DavidBessler">David Bessler</a><script data-card-contents-for-user="35315987" type="text/json">{"id":35315987,"first_name":"David","last_name":"Bessler","domain_name":"independent","page_name":"DavidBessler","display_name":"David Bessler","profile_url":"https://independent.academia.edu/DavidBessler?f_ri=725","photo":"/images/s65_no_pic.png"}</script></span></span></li><li class="js-paper-rank-work_25508105 InlineList-item InlineList-item--bordered hidden"><span class="js-paper-rank-view hidden u-tcGrayDark" data-paper-rank-work-id="25508105"><i class="u-m1x fa fa-bar-chart"></i><strong class="js-paper-rank"></strong></span><script>$(function() { new Works.PaperRankView({ workId: 25508105, container: ".js-paper-rank-work_25508105", }); 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$(".js-view-count[data-work-id=25508105]").text(description); $(".js-view-count-work_25508105").attr('title', description).tooltip(); }); });</script></span><script>$(function() { $(".js-view-count-work_25508105").removeClass('hidden') })</script></div></li><li class="InlineList-item u-positionRelative" style="max-width: 250px"><div class="u-positionAbsolute" data-has-card-for-ri-list="25508105"><i class="fa fa-tag InlineList-item-icon u-positionRelative"></i>  <a class="InlineList-item-text u-positionRelative">7</a>  </div><span class="InlineList-item-text u-textTruncate u-pl9x"><a class="InlineList-item-text" data-has-card-for-ri="725" rel="nofollow" href="https://www.academia.edu/Documents/in/Computational_Economics">Computational Economics</a>, <script data-card-contents-for-ri="725" type="text/json">{"id":725,"name":"Computational Economics","url":"https://www.academia.edu/Documents/in/Computational_Economics?f_ri=725","nofollow":true}</script><a class="InlineList-item-text" data-has-card-for-ri="747" rel="nofollow" href="https://www.academia.edu/Documents/in/Econometrics">Econometrics</a>, <script data-card-contents-for-ri="747" type="text/json">{"id":747,"name":"Econometrics","url":"https://www.academia.edu/Documents/in/Econometrics?f_ri=725","nofollow":true}</script><a class="InlineList-item-text" data-has-card-for-ri="2008" rel="nofollow" href="https://www.academia.edu/Documents/in/Machine_Learning">Machine Learning</a>, <script data-card-contents-for-ri="2008" type="text/json">{"id":2008,"name":"Machine Learning","url":"https://www.academia.edu/Documents/in/Machine_Learning?f_ri=725","nofollow":true}</script><a class="InlineList-item-text" data-has-card-for-ri="28523" rel="nofollow" href="https://www.academia.edu/Documents/in/Causal_Inference">Causal Inference</a><script data-card-contents-for-ri="28523" type="text/json">{"id":28523,"name":"Causal Inference","url":"https://www.academia.edu/Documents/in/Causal_Inference?f_ri=725","nofollow":true}</script></span></li><script>(function(){ if (true) { new Aedu.ResearchInterestListCard({ el: $('*[data-has-card-for-ri-list=25508105]'), work: {"id":25508105,"title":"Graphical Methods, Inductive Causal Inference, and Econometrics: A Literature Review","created_at":"2016-05-21T05:17:37.903-07:00","url":"https://www.academia.edu/25508105/Graphical_Methods_Inductive_Causal_Inference_and_Econometrics_A_Literature_Review?f_ri=725","dom_id":"work_25508105","summary":"Recent work with graphical methods for inductive causal inference with observational econometric data is reviewed and compared with earlier work. Two alternative algorithms are described. Caveats on applications are discussed.","downloadable_attachments":[{"id":45829925,"asset_id":25508105,"asset_type":"Work","always_allow_download":false}],"ordered_authors":[{"id":35315987,"first_name":"David","last_name":"Bessler","domain_name":"independent","page_name":"DavidBessler","display_name":"David Bessler","profile_url":"https://independent.academia.edu/DavidBessler?f_ri=725","photo":"/images/s65_no_pic.png"}],"research_interests":[{"id":725,"name":"Computational Economics","url":"https://www.academia.edu/Documents/in/Computational_Economics?f_ri=725","nofollow":true},{"id":747,"name":"Econometrics","url":"https://www.academia.edu/Documents/in/Econometrics?f_ri=725","nofollow":true},{"id":2008,"name":"Machine Learning","url":"https://www.academia.edu/Documents/in/Machine_Learning?f_ri=725","nofollow":true},{"id":28523,"name":"Causal Inference","url":"https://www.academia.edu/Documents/in/Causal_Inference?f_ri=725","nofollow":true},{"id":44293,"name":"Literature Review","url":"https://www.academia.edu/Documents/in/Literature_Review?f_ri=725"},{"id":2143462,"name":"Directed Acyclic Graph","url":"https://www.academia.edu/Documents/in/Directed_Acyclic_Graph?f_ri=725"},{"id":2377358,"name":"Graphical Method","url":"https://www.academia.edu/Documents/in/Graphical_Method?f_ri=725"}]}, }) } })();</script></ul></li></ul></div></div><div class="u-borderBottom1 u-borderColorGrayLighter"><div class="clearfix u-pv7x u-mb0x js-work-card work_30814779" data-work_id="30814779" itemscope="itemscope" itemtype="https://schema.org/ScholarlyArticle"><div class="header"><div class="title u-fontSerif u-fs22 u-lineHeight1_3"><a class="u-tcGrayDarkest js-work-link" href="https://www.academia.edu/30814779/Emergent_Complexity_in_Agent_Based_Computational_Economics">Emergent Complexity in Agent-Based Computational Economics</a></div></div><div class="u-pb4x u-mt3x"><div class="summary u-fs14 u-fw300 u-lineHeight1_5 u-tcGrayDarkest"><div class="summarized">In this paper, we shall review two kinds of emergent complexity in agent-based computational economics (ACE). The first kind is based on the complex systems initiated in the 1980s or even earlier by mathematicians and physicists, whereas... <a class="more_link u-tcGrayDark u-linkUnstyled" data-container=".work_30814779" data-show=".complete" data-hide=".summarized" data-more-link-behavior="true" href="#">more</a></div><div class="complete hidden">In this paper, we shall review two kinds of emergent complexity in agent-based computational economics (ACE). The first kind is based on the complex systems initiated in the 1980s or even earlier by mathematicians and physicists, whereas the second kind is based on the idea of complex adaptive systems composed of autonomous agents, for which many representative works have been collected in Rosser. For the latter, we shall go further to examine the two elements which have just recently been incorporated in agent-based economic modelling, namely, intelligence and modularity. This augmentation leads to the development of neurocognitive software agents, which can guide the generation and direction of future ACE studies with a multistage 'brain/behaviourto-emergency-to-brain/behaviour' approach.</div></div></div><ul class="InlineList u-ph0x u-fs13"><li class="InlineList-item logged_in_only"><div class="share_on_academia_work_button"><a class="academia_share Button Button--inverseBlue Button--sm js-bookmark-button" data-academia-share="Work/30814779" data-share-source="work_strip" data-spinner="small_white_hide_contents"><i class="fa fa-plus"></i><span class="work-strip-link-text u-ml1x" data-content="button_text">Bookmark</span></a></div></li><li class="InlineList-item"><div class="download"><a id="0d0ead11859187f142d9c64c34999fd1" rel="nofollow" data-download="{"attachment_id":51248167,"asset_id":30814779,"asset_type":"Work","always_allow_download":false,"track":null,"button_location":"work_strip","source":null,"hide_modal":null}" class="Button Button--sm Button--inverseGreen js-download-button prompt_button doc_download" href="https://www.academia.edu/attachments/51248167/download_file?st=MTc0MDU1NDYwMCw4LjIyMi4yMDguMTQ2&s=work_strip"><i class="fa fa-arrow-circle-o-down fa-lg"></i><span class="u-textUppercase u-ml1x" data-content="button_text">Download</span></a></div></li><li class="InlineList-item"><ul class="InlineList InlineList--bordered u-ph0x"><li class="InlineList-item InlineList-item--bordered"><span class="InlineList-item-text">by <span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a class="u-tcGrayDark u-fw700" data-has-card-for-user="12978461" href="https://erenlai.academia.edu/ShuHengChen">Shu-Heng Chen</a><script data-card-contents-for-user="12978461" type="text/json">{"id":12978461,"first_name":"Shu-Heng","last_name":"Chen","domain_name":"erenlai","page_name":"ShuHengChen","display_name":"Shu-Heng Chen","profile_url":"https://erenlai.academia.edu/ShuHengChen?f_ri=725","photo":"/images/s65_no_pic.png"}</script></span></span></li><li class="js-paper-rank-work_30814779 InlineList-item InlineList-item--bordered hidden"><span class="js-paper-rank-view hidden u-tcGrayDark" data-paper-rank-work-id="30814779"><i class="u-m1x fa fa-bar-chart"></i><strong class="js-paper-rank"></strong></span><script>$(function() { new Works.PaperRankView({ workId: 30814779, container: ".js-paper-rank-work_30814779", }); 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The first kind is based on the complex systems initiated in the 1980s or even earlier by mathematicians and physicists, whereas the second kind is based on the idea of complex adaptive systems composed of autonomous agents, for which many representative works have been collected in Rosser. For the latter, we shall go further to examine the two elements which have just recently been incorporated in agent-based economic modelling, namely, intelligence and modularity. This augmentation leads to the development of neurocognitive software agents, which can guide the generation and direction of future ACE studies with a multistage 'brain/behaviourto-emergency-to-brain/behaviour' approach.","downloadable_attachments":[{"id":51248167,"asset_id":30814779,"asset_type":"Work","always_allow_download":false}],"ordered_authors":[{"id":12978461,"first_name":"Shu-Heng","last_name":"Chen","domain_name":"erenlai","page_name":"ShuHengChen","display_name":"Shu-Heng Chen","profile_url":"https://erenlai.academia.edu/ShuHengChen?f_ri=725","photo":"/images/s65_no_pic.png"}],"research_interests":[{"id":725,"name":"Computational Economics","url":"https://www.academia.edu/Documents/in/Computational_Economics?f_ri=725","nofollow":true},{"id":747,"name":"Econometrics","url":"https://www.academia.edu/Documents/in/Econometrics?f_ri=725","nofollow":true},{"id":27659,"name":"Applied Economics","url":"https://www.academia.edu/Documents/in/Applied_Economics?f_ri=725","nofollow":true},{"id":54501,"name":"Complex System","url":"https://www.academia.edu/Documents/in/Complex_System?f_ri=725","nofollow":true},{"id":256303,"name":"Complex Adaptive System","url":"https://www.academia.edu/Documents/in/Complex_Adaptive_System?f_ri=725"},{"id":290495,"name":"Software Agent","url":"https://www.academia.edu/Documents/in/Software_Agent?f_ri=725"}]}, }) } })();</script></ul></li></ul></div></div><div class="u-borderBottom1 u-borderColorGrayLighter"><div class="clearfix u-pv7x u-mb0x js-work-card work_1175620" data-work_id="1175620" itemscope="itemscope" itemtype="https://schema.org/ScholarlyArticle"><div class="header"><div class="title u-fontSerif u-fs22 u-lineHeight1_3"><a class="u-tcGrayDarkest js-work-link" href="https://www.academia.edu/1175620/A_new_convergence_theorem_for_successive_overrelaxation_iterations">A new convergence theorem for successive overrelaxation iterations</a></div></div><div class="u-pb4x u-mt3x"><div class="summary u-fs14 u-fw300 u-lineHeight1_5 u-tcGrayDarkest"><div class="summarized">This paper contains a new convergence theorem for Gauss-Seidel (SOR) iterations for an arbitrary equation system. We use that theorem to show how to reorder equations and to extend their radius of convergence. It is not generally optimal... <a class="more_link u-tcGrayDark u-linkUnstyled" data-container=".work_1175620" data-show=".complete" data-hide=".summarized" data-more-link-behavior="true" href="#">more</a></div><div class="complete hidden">This paper contains a new convergence theorem for Gauss-Seidel (SOR) iterations for an arbitrary equation system. We use that theorem to show how to reorder equations and to extend their radius of convergence. It is not generally optimal to minimise the number or size of the above diagonal elements in a non-recursive system.</div></div></div><ul class="InlineList u-ph0x u-fs13"><li class="InlineList-item logged_in_only"><div class="share_on_academia_work_button"><a class="academia_share Button Button--inverseBlue Button--sm js-bookmark-button" data-academia-share="Work/1175620" data-share-source="work_strip" data-spinner="small_white_hide_contents"><i class="fa fa-plus"></i><span class="work-strip-link-text u-ml1x" data-content="button_text">Bookmark</span></a></div></li><li class="InlineList-item"><div class="download"><a id="691580d60df41e86ac5ca8f41cbb69a9" rel="nofollow" data-download="{"attachment_id":51071516,"asset_id":1175620,"asset_type":"Work","always_allow_download":false,"track":null,"button_location":"work_strip","source":null,"hide_modal":null}" class="Button Button--sm Button--inverseGreen js-download-button prompt_button doc_download" href="https://www.academia.edu/attachments/51071516/download_file?st=MTc0MDU1NDYwMCw4LjIyMi4yMDguMTQ2&s=work_strip"><i class="fa fa-arrow-circle-o-down fa-lg"></i><span class="u-textUppercase u-ml1x" data-content="button_text">Download</span></a></div></li><li class="InlineList-item"><ul class="InlineList InlineList--bordered u-ph0x"><li class="InlineList-item InlineList-item--bordered"><span class="InlineList-item-text">by <span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a class="u-tcGrayDark u-fw700" data-has-card-for-user="1067907" href="https://independent.academia.edu/laurapiscitelli">laura piscitelli</a><script data-card-contents-for-user="1067907" type="text/json">{"id":1067907,"first_name":"laura","last_name":"piscitelli","domain_name":"independent","page_name":"laurapiscitelli","display_name":"laura piscitelli","profile_url":"https://independent.academia.edu/laurapiscitelli?f_ri=725","photo":"/images/s65_no_pic.png"}</script></span></span></li><li class="js-paper-rank-work_1175620 InlineList-item InlineList-item--bordered hidden"><span class="js-paper-rank-view hidden u-tcGrayDark" data-paper-rank-work-id="1175620"><i class="u-m1x fa fa-bar-chart"></i><strong class="js-paper-rank"></strong></span><script>$(function() { new Works.PaperRankView({ workId: 1175620, container: ".js-paper-rank-work_1175620", }); 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We use that theorem to show how to reorder equations and to extend their radius of convergence. It is not generally optimal to minimise the number or size of the above diagonal elements in a non-recursive system.","downloadable_attachments":[{"id":51071516,"asset_id":1175620,"asset_type":"Work","always_allow_download":false}],"ordered_authors":[{"id":1067907,"first_name":"laura","last_name":"piscitelli","domain_name":"independent","page_name":"laurapiscitelli","display_name":"laura piscitelli","profile_url":"https://independent.academia.edu/laurapiscitelli?f_ri=725","photo":"/images/s65_no_pic.png"}],"research_interests":[{"id":725,"name":"Computational Economics","url":"https://www.academia.edu/Documents/in/Computational_Economics?f_ri=725","nofollow":true},{"id":747,"name":"Econometrics","url":"https://www.academia.edu/Documents/in/Econometrics?f_ri=725","nofollow":true}]}, }) } })();</script></ul></li></ul></div></div><div class="u-borderBottom1 u-borderColorGrayLighter"><div class="clearfix u-pv7x u-mb0x js-work-card work_21382027" data-work_id="21382027" itemscope="itemscope" itemtype="https://schema.org/ScholarlyArticle"><div class="header"><div class="title u-fontSerif u-fs22 u-lineHeight1_3"><a class="u-tcGrayDarkest js-work-link" href="https://www.academia.edu/21382027/Computation_of_Equilibria_in_OLG_Models_with_Many_Heterogeneous_Households">Computation of Equilibria in OLG Models with Many Heterogeneous Households</a></div></div><div class="u-pb4x u-mt3x"><div class="summary u-fs14 u-fw300 u-lineHeight1_5 u-tcGrayDarkest"><div class="summarized">... Negishi&#x27;s original paper was primarily concerned with optimization as a means of proving existence. Dixon (1975) developed the theory and computational effectiveness of joint maximization algorithms for multi-country trade... <a class="more_link u-tcGrayDark u-linkUnstyled" data-container=".work_21382027" data-show=".complete" data-hide=".summarized" data-more-link-behavior="true" href="#">more</a></div><div class="complete hidden">... Negishi&#x27;s original paper was primarily concerned with optimization as a means of proving existence. Dixon (1975) developed the theory and computational effectiveness of joint maximization algorithms for multi-country trade models. ...</div></div></div><ul class="InlineList u-ph0x u-fs13"><li class="InlineList-item logged_in_only"><div class="share_on_academia_work_button"><a class="academia_share Button Button--inverseBlue Button--sm js-bookmark-button" data-academia-share="Work/21382027" data-share-source="work_strip" data-spinner="small_white_hide_contents"><i class="fa fa-plus"></i><span class="work-strip-link-text u-ml1x" data-content="button_text">Bookmark</span></a></div></li><li class="InlineList-item"><div class="download"><a id="202c846a0b5d694f0a20a0f5cc57af38" rel="nofollow" data-download="{"attachment_id":41902148,"asset_id":21382027,"asset_type":"Work","always_allow_download":false,"track":null,"button_location":"work_strip","source":null,"hide_modal":null}" class="Button Button--sm Button--inverseGreen js-download-button prompt_button doc_download" href="https://www.academia.edu/attachments/41902148/download_file?st=MTc0MDU1NDYwMCw4LjIyMi4yMDguMTQ2&s=work_strip"><i class="fa fa-arrow-circle-o-down fa-lg"></i><span class="u-textUppercase u-ml1x" data-content="button_text">Download</span></a></div></li><li class="InlineList-item"><ul class="InlineList InlineList--bordered u-ph0x"><li class="InlineList-item InlineList-item--bordered"><span class="InlineList-item-text">by <span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a class="u-tcGrayDark u-fw700" data-has-card-for-user="42457656" href="https://independent.academia.edu/SebastianRausch">Sebastian Rausch</a><script data-card-contents-for-user="42457656" type="text/json">{"id":42457656,"first_name":"Sebastian","last_name":"Rausch","domain_name":"independent","page_name":"SebastianRausch","display_name":"Sebastian Rausch","profile_url":"https://independent.academia.edu/SebastianRausch?f_ri=725","photo":"/images/s65_no_pic.png"}</script></span></span></li><li class="js-paper-rank-work_21382027 InlineList-item InlineList-item--bordered hidden"><span class="js-paper-rank-view hidden u-tcGrayDark" data-paper-rank-work-id="21382027"><i class="u-m1x fa fa-bar-chart"></i><strong class="js-paper-rank"></strong></span><script>$(function() { new Works.PaperRankView({ workId: 21382027, container: ".js-paper-rank-work_21382027", }); 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$(".js-view-count[data-work-id=21382027]").text(description); $(".js-view-count-work_21382027").attr('title', description).tooltip(); }); });</script></span><script>$(function() { $(".js-view-count-work_21382027").removeClass('hidden') })</script></div></li><li class="InlineList-item u-positionRelative" style="max-width: 250px"><div class="u-positionAbsolute" data-has-card-for-ri-list="21382027"><i class="fa fa-tag InlineList-item-icon u-positionRelative"></i>  <a class="InlineList-item-text u-positionRelative">5</a>  </div><span class="InlineList-item-text u-textTruncate u-pl9x"><a class="InlineList-item-text" data-has-card-for-ri="725" rel="nofollow" href="https://www.academia.edu/Documents/in/Computational_Economics">Computational Economics</a>, <script data-card-contents-for-ri="725" type="text/json">{"id":725,"name":"Computational Economics","url":"https://www.academia.edu/Documents/in/Computational_Economics?f_ri=725","nofollow":true}</script><a class="InlineList-item-text" data-has-card-for-ri="747" rel="nofollow" href="https://www.academia.edu/Documents/in/Econometrics">Econometrics</a>, <script data-card-contents-for-ri="747" type="text/json">{"id":747,"name":"Econometrics","url":"https://www.academia.edu/Documents/in/Econometrics?f_ri=725","nofollow":true}</script><a class="InlineList-item-text" data-has-card-for-ri="79158" rel="nofollow" href="https://www.academia.edu/Documents/in/Computable_General_Equilibrium">Computable General Equilibrium</a>, <script data-card-contents-for-ri="79158" type="text/json">{"id":79158,"name":"Computable General Equilibrium","url":"https://www.academia.edu/Documents/in/Computable_General_Equilibrium?f_ri=725","nofollow":true}</script><a class="InlineList-item-text" data-has-card-for-ri="147612" rel="nofollow" href="https://www.academia.edu/Documents/in/Market_economy">Market economy</a><script data-card-contents-for-ri="147612" type="text/json">{"id":147612,"name":"Market economy","url":"https://www.academia.edu/Documents/in/Market_economy?f_ri=725","nofollow":true}</script></span></li><script>(function(){ if (true) { new Aedu.ResearchInterestListCard({ el: $('*[data-has-card-for-ri-list=21382027]'), work: {"id":21382027,"title":"Computation of Equilibria in OLG Models with Many Heterogeneous Households","created_at":"2016-02-01T02:22:29.327-08:00","url":"https://www.academia.edu/21382027/Computation_of_Equilibria_in_OLG_Models_with_Many_Heterogeneous_Households?f_ri=725","dom_id":"work_21382027","summary":"... Negishi\u0026#x27;s original paper was primarily concerned with optimization as a means of proving existence. Dixon (1975) developed the theory and computational effectiveness of joint maximization algorithms for multi-country trade models. ...","downloadable_attachments":[{"id":41902148,"asset_id":21382027,"asset_type":"Work","always_allow_download":false}],"ordered_authors":[{"id":42457656,"first_name":"Sebastian","last_name":"Rausch","domain_name":"independent","page_name":"SebastianRausch","display_name":"Sebastian Rausch","profile_url":"https://independent.academia.edu/SebastianRausch?f_ri=725","photo":"/images/s65_no_pic.png"}],"research_interests":[{"id":725,"name":"Computational Economics","url":"https://www.academia.edu/Documents/in/Computational_Economics?f_ri=725","nofollow":true},{"id":747,"name":"Econometrics","url":"https://www.academia.edu/Documents/in/Econometrics?f_ri=725","nofollow":true},{"id":79158,"name":"Computable General Equilibrium","url":"https://www.academia.edu/Documents/in/Computable_General_Equilibrium?f_ri=725","nofollow":true},{"id":147612,"name":"Market economy","url":"https://www.academia.edu/Documents/in/Market_economy?f_ri=725","nofollow":true},{"id":1438584,"name":"Overlapping Generations Model","url":"https://www.academia.edu/Documents/in/Overlapping_Generations_Model?f_ri=725"}]}, }) } })();</script></ul></li></ul></div></div><div class="u-borderBottom1 u-borderColorGrayLighter"><div class="clearfix u-pv7x u-mb0x js-work-card work_30343388" data-work_id="30343388" itemscope="itemscope" itemtype="https://schema.org/ScholarlyArticle"><div class="header"><div class="title u-fontSerif u-fs22 u-lineHeight1_3"><a class="u-tcGrayDarkest js-work-link" href="https://www.academia.edu/30343388/Optimal_Prediction_with_Conditionally_Heteroskedastic_Factor_Analysed_Hidden_Markov_Models">Optimal Prediction with Conditionally Heteroskedastic Factor Analysed Hidden Markov Models</a></div></div><div class="u-pb4x u-mt3x"><div class="summary u-fs14 u-fw300 u-lineHeight1_5 u-tcGrayDarkest"><div class="summarized">The deficiencies of stationary models applied to financial time series are well documented. A special form of non-stationarity, where the underlying generator switches between (approximately) stationary regimes, seems particularly... <a class="more_link u-tcGrayDark u-linkUnstyled" data-container=".work_30343388" data-show=".complete" data-hide=".summarized" data-more-link-behavior="true" href="#">more</a></div><div class="complete hidden">The deficiencies of stationary models applied to financial time series are well documented. A special form of non-stationarity, where the underlying generator switches between (approximately) stationary regimes, seems particularly appropriate for financial markets. We use a dynamic switching (modelled by a hidden Markov model) combined with a linear conditionally heteroskedastic latent factor model in a hybrid conditionally heteroskedastic factor analysed hidden Markov model (CHFAHMM) and discuss the practical details of training such models with a new approximated version of the Viterbi algorithm in conjunction with the expectationmaximization algorithm to iteratively estimate the model parameters in a maximumlikelihood sense. The performance of the CHFAHMM is evaluated on both simulated and financial data sets. On the basis of out-of-sample forecast encompassing tests as well as other measures for forecasting accuracy, our results indicate that the use of this new method yields overall better forecasts than those generated by competing models.</div></div></div><ul class="InlineList u-ph0x u-fs13"><li class="InlineList-item logged_in_only"><div class="share_on_academia_work_button"><a class="academia_share Button Button--inverseBlue Button--sm js-bookmark-button" data-academia-share="Work/30343388" data-share-source="work_strip" data-spinner="small_white_hide_contents"><i class="fa fa-plus"></i><span class="work-strip-link-text u-ml1x" data-content="button_text">Bookmark</span></a></div></li><li class="InlineList-item"><div class="download"><a id="c48ae23cf0024c3d93352d4cd47a4b41" rel="nofollow" data-download="{"attachment_id":50796761,"asset_id":30343388,"asset_type":"Work","always_allow_download":false,"track":null,"button_location":"work_strip","source":null,"hide_modal":null}" class="Button Button--sm Button--inverseGreen js-download-button prompt_button doc_download" href="https://www.academia.edu/attachments/50796761/download_file?st=MTc0MDU1NDYwMCw4LjIyMi4yMDguMTQ2&s=work_strip"><i class="fa fa-arrow-circle-o-down fa-lg"></i><span class="u-textUppercase u-ml1x" data-content="button_text">Download</span></a></div></li><li class="InlineList-item"><ul class="InlineList InlineList--bordered u-ph0x"><li class="InlineList-item InlineList-item--bordered"><span class="InlineList-item-text">by <span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a class="u-tcGrayDark u-fw700" data-has-card-for-user="57752485" href="https://independent.academia.edu/ChristianLavergne">Christian Lavergne</a><script data-card-contents-for-user="57752485" type="text/json">{"id":57752485,"first_name":"Christian","last_name":"Lavergne","domain_name":"independent","page_name":"ChristianLavergne","display_name":"Christian Lavergne","profile_url":"https://independent.academia.edu/ChristianLavergne?f_ri=725","photo":"/images/s65_no_pic.png"}</script></span></span></li><li class="js-paper-rank-work_30343388 InlineList-item InlineList-item--bordered hidden"><span class="js-paper-rank-view hidden u-tcGrayDark" data-paper-rank-work-id="30343388"><i class="u-m1x fa fa-bar-chart"></i><strong class="js-paper-rank"></strong></span><script>$(function() { new Works.PaperRankView({ workId: 30343388, container: ".js-paper-rank-work_30343388", }); 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$(".js-view-count[data-work-id=30343388]").text(description); $(".js-view-count-work_30343388").attr('title', description).tooltip(); }); });</script></span><script>$(function() { $(".js-view-count-work_30343388").removeClass('hidden') })</script></div></li><li class="InlineList-item u-positionRelative" style="max-width: 250px"><div class="u-positionAbsolute" data-has-card-for-ri-list="30343388"><i class="fa fa-tag InlineList-item-icon u-positionRelative"></i>  <a class="InlineList-item-text u-positionRelative">12</a>  </div><span class="InlineList-item-text u-textTruncate u-pl10x"><a class="InlineList-item-text" data-has-card-for-ri="725" rel="nofollow" href="https://www.academia.edu/Documents/in/Computational_Economics">Computational Economics</a>, <script data-card-contents-for-ri="725" type="text/json">{"id":725,"name":"Computational Economics","url":"https://www.academia.edu/Documents/in/Computational_Economics?f_ri=725","nofollow":true}</script><a class="InlineList-item-text" data-has-card-for-ri="747" rel="nofollow" href="https://www.academia.edu/Documents/in/Econometrics">Econometrics</a>, <script data-card-contents-for-ri="747" type="text/json">{"id":747,"name":"Econometrics","url":"https://www.academia.edu/Documents/in/Econometrics?f_ri=725","nofollow":true}</script><a class="InlineList-item-text" data-has-card-for-ri="4456" rel="nofollow" href="https://www.academia.edu/Documents/in/Time_Series">Time Series</a>, <script data-card-contents-for-ri="4456" type="text/json">{"id":4456,"name":"Time Series","url":"https://www.academia.edu/Documents/in/Time_Series?f_ri=725","nofollow":true}</script><a class="InlineList-item-text" data-has-card-for-ri="8270" rel="nofollow" href="https://www.academia.edu/Documents/in/Forecasting">Forecasting</a><script data-card-contents-for-ri="8270" type="text/json">{"id":8270,"name":"Forecasting","url":"https://www.academia.edu/Documents/in/Forecasting?f_ri=725","nofollow":true}</script></span></li><script>(function(){ if (true) { new Aedu.ResearchInterestListCard({ el: $('*[data-has-card-for-ri-list=30343388]'), work: {"id":30343388,"title":"Optimal Prediction with Conditionally Heteroskedastic Factor Analysed Hidden Markov Models","created_at":"2016-12-08T23:55:33.946-08:00","url":"https://www.academia.edu/30343388/Optimal_Prediction_with_Conditionally_Heteroskedastic_Factor_Analysed_Hidden_Markov_Models?f_ri=725","dom_id":"work_30343388","summary":"The deficiencies of stationary models applied to financial time series are well documented. A special form of non-stationarity, where the underlying generator switches between (approximately) stationary regimes, seems particularly appropriate for financial markets. We use a dynamic switching (modelled by a hidden Markov model) combined with a linear conditionally heteroskedastic latent factor model in a hybrid conditionally heteroskedastic factor analysed hidden Markov model (CHFAHMM) and discuss the practical details of training such models with a new approximated version of the Viterbi algorithm in conjunction with the expectationmaximization algorithm to iteratively estimate the model parameters in a maximumlikelihood sense. The performance of the CHFAHMM is evaluated on both simulated and financial data sets. On the basis of out-of-sample forecast encompassing tests as well as other measures for forecasting accuracy, our results indicate that the use of this new method yields overall better forecasts than those generated by competing models.","downloadable_attachments":[{"id":50796761,"asset_id":30343388,"asset_type":"Work","always_allow_download":false}],"ordered_authors":[{"id":57752485,"first_name":"Christian","last_name":"Lavergne","domain_name":"independent","page_name":"ChristianLavergne","display_name":"Christian Lavergne","profile_url":"https://independent.academia.edu/ChristianLavergne?f_ri=725","photo":"/images/s65_no_pic.png"}],"research_interests":[{"id":725,"name":"Computational Economics","url":"https://www.academia.edu/Documents/in/Computational_Economics?f_ri=725","nofollow":true},{"id":747,"name":"Econometrics","url":"https://www.academia.edu/Documents/in/Econometrics?f_ri=725","nofollow":true},{"id":4456,"name":"Time Series","url":"https://www.academia.edu/Documents/in/Time_Series?f_ri=725","nofollow":true},{"id":8270,"name":"Forecasting","url":"https://www.academia.edu/Documents/in/Forecasting?f_ri=725","nofollow":true},{"id":61227,"name":"Financial time series","url":"https://www.academia.edu/Documents/in/Financial_time_series?f_ri=725"},{"id":87364,"name":"Maximum Likelihood","url":"https://www.academia.edu/Documents/in/Maximum_Likelihood?f_ri=725"},{"id":143539,"name":"hidden Markov model","url":"https://www.academia.edu/Documents/in/hidden_Markov_model?f_ri=725"},{"id":149438,"name":"EM algorithm","url":"https://www.academia.edu/Documents/in/EM_algorithm?f_ri=725"},{"id":195152,"name":"Hmm","url":"https://www.academia.edu/Documents/in/Hmm?f_ri=725"},{"id":207888,"name":"Viterbi algorithm","url":"https://www.academia.edu/Documents/in/Viterbi_algorithm?f_ri=725"},{"id":270673,"name":"Financial Market","url":"https://www.academia.edu/Documents/in/Financial_Market?f_ri=725"},{"id":1001151,"name":"Expectation Maximization (EM) Algorithm","url":"https://www.academia.edu/Documents/in/Expectation_Maximization_EM_Algorithm?f_ri=725"}]}, }) } })();</script></ul></li></ul></div></div><div class="u-borderBottom1 u-borderColorGrayLighter"><div class="clearfix u-pv7x u-mb0x js-work-card work_11410957" data-work_id="11410957" itemscope="itemscope" itemtype="https://schema.org/ScholarlyArticle"><div class="header"><div class="title u-fontSerif u-fs22 u-lineHeight1_3"><a class="u-tcGrayDarkest js-work-link" href="https://www.academia.edu/11410957/Credit_Risk_Assessment_Using_Statistical_and_Machine_Learning_Basic_Methodology_and_Risk_Modeling_Applications">Credit Risk Assessment Using Statistical and Machine Learning: Basic Methodology and Risk Modeling Applications</a></div></div><div class="u-pb4x u-mt3x"><div class="summary u-fs14 u-fw300 u-lineHeight1_5 u-tcGrayDarkest"><div class="summarized">Risk assessment of financialintermediaries is an area of renewed interest due tothe financial crises of the 1980's and 90's. Anaccurate estimation of risk, and its use in corporateor global financial risk models, could be translatedinto a... <a class="more_link u-tcGrayDark u-linkUnstyled" data-container=".work_11410957" data-show=".complete" data-hide=".summarized" data-more-link-behavior="true" href="#">more</a></div><div class="complete hidden">Risk assessment of financialintermediaries is an area of renewed interest due tothe financial crises of the 1980's and 90's. Anaccurate estimation of risk, and its use in corporateor global financial risk models, could be translatedinto a more efficient use of resources. One importantingredient to accomplish this goal is to find accuratepredictors of individual risk in the credit portfoliosof institutions. In this context we make a comparativeanalysis of different statistical and machine learningmodeling methods of classification on a mortgage loandata set with the motivation to understand theirlimitations and potential. We introduced a specificmodeling methodology based on the study of errorcurves. Using state-of-the-art modeling techniques webuilt more than 9,000 models as part of the study. Theresults show that CART decision-tree models providethe best estimation for default with an average 8.31%error rate for a training sample of 2,000 records. Asa result of the error curve analysis for this model weconclude that if more data were available,approximately 22,000 records, a potential 7.32% errorrate could be achieved. Neural Networks provided thesecond best results with an average error of 11.00%.The K-Nearest Neighbor algorithm had an averageerror rate of 14.95%. These results outperformed thestandard Probit algorithm which attained an averageerror rate of 15.13%. Finally we discuss thepossibilities to use this type of accurate predictivemodel as ingredients of institutional and global riskmodels.</div></div></div><ul class="InlineList u-ph0x u-fs13"><li class="InlineList-item logged_in_only"><div class="share_on_academia_work_button"><a class="academia_share Button Button--inverseBlue Button--sm js-bookmark-button" data-academia-share="Work/11410957" data-share-source="work_strip" data-spinner="small_white_hide_contents"><i class="fa fa-plus"></i><span class="work-strip-link-text u-ml1x" data-content="button_text">Bookmark</span></a></div></li><li class="InlineList-item"><div class="download"><a id="1f93a974340ce06ce11e440e5f8f851e" rel="nofollow" data-download="{"attachment_id":46723478,"asset_id":11410957,"asset_type":"Work","always_allow_download":false,"track":null,"button_location":"work_strip","source":null,"hide_modal":null}" class="Button Button--sm Button--inverseGreen js-download-button prompt_button doc_download" href="https://www.academia.edu/attachments/46723478/download_file?st=MTc0MDU1NDYwMCw4LjIyMi4yMDguMTQ2&s=work_strip"><i class="fa fa-arrow-circle-o-down fa-lg"></i><span class="u-textUppercase u-ml1x" data-content="button_text">Download</span></a></div></li><li class="InlineList-item"><ul class="InlineList InlineList--bordered u-ph0x"><li class="InlineList-item InlineList-item--bordered"><span class="InlineList-item-text">by <span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a class="u-tcGrayDark u-fw700" data-has-card-for-user="27761635" href="https://independent.academia.edu/Jos%C3%A9%C3%81ngelGalindo">José Ángel Galindo</a><script data-card-contents-for-user="27761635" type="text/json">{"id":27761635,"first_name":"José Ángel","last_name":"Galindo","domain_name":"independent","page_name":"JoséÁngelGalindo","display_name":"José Ángel Galindo","profile_url":"https://independent.academia.edu/Jos%C3%A9%C3%81ngelGalindo?f_ri=725","photo":"https://0.academia-photos.com/27761635/9256845/10319680/s65_jos_ngel.galindo.jpg"}</script></span></span></li><li class="js-paper-rank-work_11410957 InlineList-item InlineList-item--bordered hidden"><span class="js-paper-rank-view hidden u-tcGrayDark" data-paper-rank-work-id="11410957"><i class="u-m1x fa fa-bar-chart"></i><strong class="js-paper-rank"></strong></span><script>$(function() { new Works.PaperRankView({ workId: 11410957, container: ".js-paper-rank-work_11410957", }); 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$(".js-view-count[data-work-id=11410957]").text(description); $(".js-view-count-work_11410957").attr('title', description).tooltip(); }); });</script></span><script>$(function() { $(".js-view-count-work_11410957").removeClass('hidden') })</script></div></li><li class="InlineList-item u-positionRelative" style="max-width: 250px"><div class="u-positionAbsolute" data-has-card-for-ri-list="11410957"><i class="fa fa-tag InlineList-item-icon u-positionRelative"></i>  <a class="InlineList-item-text u-positionRelative">10</a>  </div><span class="InlineList-item-text u-textTruncate u-pl10x"><a class="InlineList-item-text" data-has-card-for-ri="725" rel="nofollow" href="https://www.academia.edu/Documents/in/Computational_Economics">Computational Economics</a>, <script data-card-contents-for-ri="725" type="text/json">{"id":725,"name":"Computational Economics","url":"https://www.academia.edu/Documents/in/Computational_Economics?f_ri=725","nofollow":true}</script><a class="InlineList-item-text" data-has-card-for-ri="747" rel="nofollow" href="https://www.academia.edu/Documents/in/Econometrics">Econometrics</a>, <script data-card-contents-for-ri="747" type="text/json">{"id":747,"name":"Econometrics","url":"https://www.academia.edu/Documents/in/Econometrics?f_ri=725","nofollow":true}</script><a class="InlineList-item-text" data-has-card-for-ri="2008" rel="nofollow" href="https://www.academia.edu/Documents/in/Machine_Learning">Machine Learning</a>, <script data-card-contents-for-ri="2008" type="text/json">{"id":2008,"name":"Machine Learning","url":"https://www.academia.edu/Documents/in/Machine_Learning?f_ri=725","nofollow":true}</script><a class="InlineList-item-text" data-has-card-for-ri="16664" rel="nofollow" href="https://www.academia.edu/Documents/in/Risk_assessment">Risk assessment</a><script data-card-contents-for-ri="16664" type="text/json">{"id":16664,"name":"Risk assessment","url":"https://www.academia.edu/Documents/in/Risk_assessment?f_ri=725","nofollow":true}</script></span></li><script>(function(){ if (true) { new Aedu.ResearchInterestListCard({ el: $('*[data-has-card-for-ri-list=11410957]'), work: {"id":11410957,"title":"Credit Risk Assessment Using Statistical and Machine Learning: Basic Methodology and Risk Modeling Applications","created_at":"2015-03-13T09:55:42.979-07:00","url":"https://www.academia.edu/11410957/Credit_Risk_Assessment_Using_Statistical_and_Machine_Learning_Basic_Methodology_and_Risk_Modeling_Applications?f_ri=725","dom_id":"work_11410957","summary":"Risk assessment of financialintermediaries is an area of renewed interest due tothe financial crises of the 1980's and 90's. Anaccurate estimation of risk, and its use in corporateor global financial risk models, could be translatedinto a more efficient use of resources. One importantingredient to accomplish this goal is to find accuratepredictors of individual risk in the credit portfoliosof institutions. In this context we make a comparativeanalysis of different statistical and machine learningmodeling methods of classification on a mortgage loandata set with the motivation to understand theirlimitations and potential. We introduced a specificmodeling methodology based on the study of errorcurves. Using state-of-the-art modeling techniques webuilt more than 9,000 models as part of the study. Theresults show that CART decision-tree models providethe best estimation for default with an average 8.31%error rate for a training sample of 2,000 records. Asa result of the error curve analysis for this model weconclude that if more data were available,approximately 22,000 records, a potential 7.32% errorrate could be achieved. Neural Networks provided thesecond best results with an average error of 11.00%.The K-Nearest Neighbor algorithm had an averageerror rate of 14.95%. These results outperformed thestandard Probit algorithm which attained an averageerror rate of 15.13%. Finally we discuss thepossibilities to use this type of accurate predictivemodel as ingredients of institutional and global riskmodels.","downloadable_attachments":[{"id":46723478,"asset_id":11410957,"asset_type":"Work","always_allow_download":false}],"ordered_authors":[{"id":27761635,"first_name":"José Ángel","last_name":"Galindo","domain_name":"independent","page_name":"JoséÁngelGalindo","display_name":"José Ángel Galindo","profile_url":"https://independent.academia.edu/Jos%C3%A9%C3%81ngelGalindo?f_ri=725","photo":"https://0.academia-photos.com/27761635/9256845/10319680/s65_jos_ngel.galindo.jpg"}],"research_interests":[{"id":725,"name":"Computational Economics","url":"https://www.academia.edu/Documents/in/Computational_Economics?f_ri=725","nofollow":true},{"id":747,"name":"Econometrics","url":"https://www.academia.edu/Documents/in/Econometrics?f_ri=725","nofollow":true},{"id":2008,"name":"Machine Learning","url":"https://www.academia.edu/Documents/in/Machine_Learning?f_ri=725","nofollow":true},{"id":16664,"name":"Risk assessment","url":"https://www.academia.edu/Documents/in/Risk_assessment?f_ri=725","nofollow":true},{"id":26066,"name":"Neural Network","url":"https://www.academia.edu/Documents/in/Neural_Network?f_ri=725"},{"id":85998,"name":"Credit Risk","url":"https://www.academia.edu/Documents/in/Credit_Risk?f_ri=725"},{"id":162271,"name":"Decision Tree","url":"https://www.academia.edu/Documents/in/Decision_Tree?f_ri=725"},{"id":164637,"name":"Bit Error Rate","url":"https://www.academia.edu/Documents/in/Bit_Error_Rate?f_ri=725"},{"id":269335,"name":"Financial Risk","url":"https://www.academia.edu/Documents/in/Financial_Risk?f_ri=725"},{"id":622589,"name":"Risk Assessment","url":"https://www.academia.edu/Documents/in/Risk_Assessment-2?f_ri=725"}]}, }) } })();</script></ul></li></ul></div></div><div class="u-borderBottom1 u-borderColorGrayLighter"><div class="clearfix u-pv7x u-mb0x js-work-card work_11590141" data-work_id="11590141" itemscope="itemscope" itemtype="https://schema.org/ScholarlyArticle"><div class="header"><div class="title u-fontSerif u-fs22 u-lineHeight1_3"><a class="u-tcGrayDarkest js-work-link" href="https://www.academia.edu/11590141/Econometric_and_statistical_computing_using_Ox">Econometric and statistical computing using Ox</a></div></div><div class="u-pb4x u-mt3x"><div class="summary u-fs14 u-fw300 u-lineHeight1_5 u-tcGrayDarkest"><div class="summarized">This paper reviews the matrix programming language Ox from the viewpoint of an econometrician/statistician. We focus on scientific programming using Ox and discuss examples of possible interest to econometricians and statisticians, such... <a class="more_link u-tcGrayDark u-linkUnstyled" data-container=".work_11590141" data-show=".complete" data-hide=".summarized" data-more-link-behavior="true" href="#">more</a></div><div class="complete hidden">This paper reviews the matrix programming language Ox from the viewpoint of an econometrician/statistician. We focus on scientific programming using Ox and discuss examples of possible interest to econometricians and statisticians, such as random number generation, maximum likelihood estimation, and Monte Carlo simulation. Ox is a remarkable matrix programming language which is well suited to research and teaching in econometrics and statistics.</div></div></div><ul class="InlineList u-ph0x u-fs13"><li class="InlineList-item logged_in_only"><div class="share_on_academia_work_button"><a class="academia_share Button Button--inverseBlue Button--sm js-bookmark-button" data-academia-share="Work/11590141" data-share-source="work_strip" data-spinner="small_white_hide_contents"><i class="fa fa-plus"></i><span class="work-strip-link-text u-ml1x" data-content="button_text">Bookmark</span></a></div></li><li class="InlineList-item"><div class="download"><a id="61ff7c32c7656066429705a6d4b780fb" rel="nofollow" data-download="{"attachment_id":46617112,"asset_id":11590141,"asset_type":"Work","always_allow_download":false,"track":null,"button_location":"work_strip","source":null,"hide_modal":null}" class="Button Button--sm Button--inverseGreen js-download-button prompt_button doc_download" href="https://www.academia.edu/attachments/46617112/download_file?st=MTc0MDU1NDYwMCw4LjIyMi4yMDguMTQ2&s=work_strip"><i class="fa fa-arrow-circle-o-down fa-lg"></i><span class="u-textUppercase u-ml1x" data-content="button_text">Download</span></a></div></li><li class="InlineList-item"><ul class="InlineList InlineList--bordered u-ph0x"><li class="InlineList-item InlineList-item--bordered"><span class="InlineList-item-text">by <span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a class="u-tcGrayDark u-fw700" data-has-card-for-user="28299739" href="https://independent.academia.edu/FranciscoCribarineto">Francisco Cribari-neto</a><script data-card-contents-for-user="28299739" type="text/json">{"id":28299739,"first_name":"Francisco","last_name":"Cribari-neto","domain_name":"independent","page_name":"FranciscoCribarineto","display_name":"Francisco Cribari-neto","profile_url":"https://independent.academia.edu/FranciscoCribarineto?f_ri=725","photo":"/images/s65_no_pic.png"}</script></span></span></li><li class="js-paper-rank-work_11590141 InlineList-item InlineList-item--bordered hidden"><span class="js-paper-rank-view hidden u-tcGrayDark" data-paper-rank-work-id="11590141"><i class="u-m1x fa fa-bar-chart"></i><strong class="js-paper-rank"></strong></span><script>$(function() { new Works.PaperRankView({ workId: 11590141, container: ".js-paper-rank-work_11590141", }); 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We focus on scientific programming using Ox and discuss examples of possible interest to econometricians and statisticians, such as random number generation, maximum likelihood estimation, and Monte Carlo simulation. Ox is a remarkable matrix programming language which is well suited to research and teaching in econometrics and statistics.","downloadable_attachments":[{"id":46617112,"asset_id":11590141,"asset_type":"Work","always_allow_download":false}],"ordered_authors":[{"id":28299739,"first_name":"Francisco","last_name":"Cribari-neto","domain_name":"independent","page_name":"FranciscoCribarineto","display_name":"Francisco Cribari-neto","profile_url":"https://independent.academia.edu/FranciscoCribarineto?f_ri=725","photo":"/images/s65_no_pic.png"}],"research_interests":[{"id":725,"name":"Computational Economics","url":"https://www.academia.edu/Documents/in/Computational_Economics?f_ri=725","nofollow":true},{"id":747,"name":"Econometrics","url":"https://www.academia.edu/Documents/in/Econometrics?f_ri=725","nofollow":true},{"id":1351,"name":"Statistical Computing","url":"https://www.academia.edu/Documents/in/Statistical_Computing?f_ri=725","nofollow":true},{"id":4392,"name":"Monte Carlo Simulation","url":"https://www.academia.edu/Documents/in/Monte_Carlo_Simulation?f_ri=725","nofollow":true},{"id":78300,"name":"Graphics","url":"https://www.academia.edu/Documents/in/Graphics?f_ri=725"},{"id":228350,"name":"Maximum Likelihood Estimation","url":"https://www.academia.edu/Documents/in/Maximum_Likelihood_Estimation?f_ri=725"},{"id":1123775,"name":"RANDOM NUMBER GENERATOR","url":"https://www.academia.edu/Documents/in/RANDOM_NUMBER_GENERATOR?f_ri=725"},{"id":1489478,"name":"Programming language","url":"https://www.academia.edu/Documents/in/Programming_language?f_ri=725"},{"id":1834487,"name":"C Programming Language","url":"https://www.academia.edu/Documents/in/C_Programming_Language?f_ri=725"}]}, }) } })();</script></ul></li></ul></div></div></div><div class="u-taCenter Pagination"><ul class="pagination"><li class="next_page"><a href="/Documents/in/Computational_Economics?after=50%2C11590141" rel="next">Next</a></li><li class="last next"><a 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