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indexes</title> <meta name="description" content="Search results for: stock indexes"> <meta name="keywords" content="stock indexes"> <meta name="viewport" content="width=device-width, initial-scale=1, minimum-scale=1, maximum-scale=1, user-scalable=no"> <meta charset="utf-8"> <link href="https://cdn.waset.org/favicon.ico" type="image/x-icon" rel="shortcut icon"> <link href="https://cdn.waset.org/static/plugins/bootstrap-4.2.1/css/bootstrap.min.css" rel="stylesheet"> <link href="https://cdn.waset.org/static/plugins/fontawesome/css/all.min.css" rel="stylesheet"> <link href="https://cdn.waset.org/static/css/site.css?v=150220211555" rel="stylesheet"> </head> <body> <header> <div class="container"> <nav class="navbar navbar-expand-lg navbar-light"> <a class="navbar-brand" href="https://waset.org"> <img src="https://cdn.waset.org/static/images/wasetc.png" alt="Open Science Research Excellence" title="Open Science Research Excellence" /> </a> <button class="d-block d-lg-none navbar-toggler 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id="custom-search-input"> <div class="input-group"> <i class="fas fa-search"></i> <input type="text" class="search-query" name="q" placeholder="Author, Title, Abstract, Keywords" value="stock indexes"> <input type="submit" class="btn_search" value="Search"> </div> </div> </form> </div> </div> <div class="row mt-3"> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Commenced</strong> in January 2007</div> </div> </div> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Frequency:</strong> Monthly</div> </div> </div> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Edition:</strong> International</div> </div> </div> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Paper Count:</strong> 1055</div> </div> </div> </div> <h1 class="mt-3 mb-3 text-center" style="font-size:1.6rem;">Search results for: stock indexes</h1> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1055</span> Forecasting Stock Indexes Using Bayesian Additive Regression Tree</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Darren%20Zou">Darren Zou</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Forecasting the stock market is a very challenging task. Various economic indicators such as GDP, exchange rates, interest rates, and unemployment have a substantial impact on the stock market. Time series models are the traditional methods used to predict stock market changes. In this paper, a machine learning method, Bayesian Additive Regression Tree (BART) is used in predicting stock market indexes based on multiple economic indicators. BART can be used to model heterogeneous treatment effects, and thereby works well when models are misspecified. It also has the capability to handle non-linear main effects and multi-way interactions without much input from financial analysts. In this research, BART is proposed to provide a reliable prediction on day-to-day stock market activities. By comparing the analysis results from BART and with time series method, BART can perform well and has better prediction capability than the traditional methods. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=BART" title="BART">BART</a>, <a href="https://publications.waset.org/abstracts/search?q=Bayesian" title=" Bayesian"> Bayesian</a>, <a href="https://publications.waset.org/abstracts/search?q=predict" title=" predict"> predict</a>, <a href="https://publications.waset.org/abstracts/search?q=stock" title=" stock"> stock</a> </p> <a href="https://publications.waset.org/abstracts/124504/forecasting-stock-indexes-using-bayesian-additive-regression-tree" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/124504.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">130</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1054</span> Correlation between Seismic Risk Insurance Indexes and Uninhabitability Indexes of Buildings in Morocco</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Nabil%20Mekaoui">Nabil Mekaoui</a>, <a href="https://publications.waset.org/abstracts/search?q=Nacer%20Jabour"> Nacer Jabour</a>, <a href="https://publications.waset.org/abstracts/search?q=Abdelhamid%20Allaoui"> Abdelhamid Allaoui</a>, <a href="https://publications.waset.org/abstracts/search?q=Abderahim%20Oulidi"> Abderahim Oulidi</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The reliability of several insurance indexes of the seismic risk is evaluated and compared for an efficient seismic risk coverage of buildings in Morocco, thus, reducing the basic risk. A large database of earthquake ground motions is established from recent seismic events in Morocco and synthetic ground motions compatible with the design spectrum in order to conduct nonlinear time history analyses on three building models representative of the building stock in Morocco. The uninhabitability index is evaluated based on the simulated damage index, then correlated with preselected insurance indexes. Interestingly, the commonly used peak ground acceleration index showed poor correlation when compared with other indexes, such as spectral accelerations at low periods. Recommendations on the choice of suitable insurance indexes are formulated for efficient seismic risk coverage in Morocco. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=catastrophe%20modeling" title="catastrophe modeling">catastrophe modeling</a>, <a href="https://publications.waset.org/abstracts/search?q=damage" title=" damage"> damage</a>, <a href="https://publications.waset.org/abstracts/search?q=earthquake" title=" earthquake"> earthquake</a>, <a href="https://publications.waset.org/abstracts/search?q=reinsurance" title=" reinsurance"> reinsurance</a>, <a href="https://publications.waset.org/abstracts/search?q=seismic%20hazard" title=" seismic hazard"> seismic hazard</a>, <a href="https://publications.waset.org/abstracts/search?q=trigger%20index" title=" trigger index"> trigger index</a>, <a href="https://publications.waset.org/abstracts/search?q=vulnerability" title=" vulnerability"> vulnerability</a> </p> <a href="https://publications.waset.org/abstracts/170497/correlation-between-seismic-risk-insurance-indexes-and-uninhabitability-indexes-of-buildings-in-morocco" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/170497.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">69</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1053</span> Does Pakistan Stock Exchange Offer Diversification Benefits to Regional and International Investors: A Time-Frequency (Wavelets) Analysis</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Syed%20Jawad%20Hussain%20Shahzad">Syed Jawad Hussain Shahzad</a>, <a href="https://publications.waset.org/abstracts/search?q=Muhammad%20Zakaria"> Muhammad Zakaria</a>, <a href="https://publications.waset.org/abstracts/search?q=Mobeen%20Ur%20Rehman"> Mobeen Ur Rehman</a>, <a href="https://publications.waset.org/abstracts/search?q=Saniya%20Khaild"> Saniya Khaild</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This study examines the co-movement between the Pakistan, Indian, S&P 500 and Nikkei 225 stock markets using weekly data from 1998 to 2013. The time-frequency relationship between the selected stock markets is conducted by using measures of continuous wavelet power spectrum, cross-wavelet transform and cross (squared) wavelet coherency. The empirical evidence suggests strong dependence between Pakistan and Indian stock markets. The co-movement of Pakistani index with U.S and Japanese, the developed markets, varies over time and frequency where the long-run relationship is dominant. The results of cross wavelet and wavelet coherence analysis indicate moderate covariance and correlation between stock indexes and the markets are in phase (i.e. cyclical in nature) over varying durations. Pakistan stock market was lagging during the entire period in relation to Indian stock market, corresponding to the 8~32 and then 64~256 weeks scale. Similar findings are evident for S&P 500 and Nikkei 225 indexes, however, the relationship occurs during the later period of study. All three wavelet indicators suggest strong evidence of higher co-movement during 2008-09 global financial crises. The empirical analysis reveals a strong evidence that the portfolio diversification benefits vary across frequencies and time. This analysis is unique and have several practical implications for regional and international investors while assigning the optimal weightage of different assets in portfolio formulation. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=co-movement" title="co-movement">co-movement</a>, <a href="https://publications.waset.org/abstracts/search?q=Pakistan%20stock%20exchange" title=" Pakistan stock exchange"> Pakistan stock exchange</a>, <a href="https://publications.waset.org/abstracts/search?q=S%26P%20500" title=" S&P 500"> S&P 500</a>, <a href="https://publications.waset.org/abstracts/search?q=Nikkei%20225" title=" Nikkei 225"> Nikkei 225</a>, <a href="https://publications.waset.org/abstracts/search?q=wavelet%20analysis" title=" wavelet analysis"> wavelet analysis</a> </p> <a href="https://publications.waset.org/abstracts/30445/does-pakistan-stock-exchange-offer-diversification-benefits-to-regional-and-international-investors-a-time-frequency-wavelets-analysis" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/30445.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">357</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1052</span> Causality between Stock Indices and Cryptocurrencies during the Russia-Ukraine War</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Nidhal%20Mgadmi">Nidhal Mgadmi</a>, <a href="https://publications.waset.org/abstracts/search?q=Abdelhafidh%20Othmani"> Abdelhafidh Othmani</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This article examines the causal relationship between stock indices and cryptocurrencies during the current war between Russia and Ukraine. The econometric investigation runs from February 24, 2022, to April 12, 2023, focusing on seven stock market indices (S&P500, DAX, CAC40, Nikkei, TSX, MOEX, and PFTS) and seven cryptocurrencies (Bitcoin, Ethereum, Litcoin, Dash, Ripple, DigiByte and XEM). In this article, we try to understand how investors react to fluctuations in financial assets to seek safe havens in cryptocurrencies. We used dynamic causality to detect a possible causal relationship in the short term and seven models to estimate the long-term relationship between cryptocurrencies and financial assets. The causal relationship between financial market indexes and cryptocurrency coins in the short run indicates that three famous cryptocurrencies (BITCOIN, ETHEREUM, RIPPLE) and the two digital assets with minor popularity (XEM, Digibyte) are impacted by the German, Russian, and Ukrainian stock markets. In the long run, we found a positive and significate effect of the American, Canadian, French, and Ukrainian stock market indexes on Bitcoin. Thus, the stability of the traditional financial markets during the current war period can be explained on the one hand by investors’ fears of an unstable business climate, and on the other hand, by speculators’ sentiment towards new electronic products, which are perceived as hedging instruments and a safe haven in the face of the conflict between Ukraine and Russia. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=causality" title="causality">causality</a>, <a href="https://publications.waset.org/abstracts/search?q=stock%20indices" title=" stock indices"> stock indices</a>, <a href="https://publications.waset.org/abstracts/search?q=cryptocurrency" title=" cryptocurrency"> cryptocurrency</a>, <a href="https://publications.waset.org/abstracts/search?q=war" title=" war"> war</a>, <a href="https://publications.waset.org/abstracts/search?q=Russia" title=" Russia"> Russia</a>, <a href="https://publications.waset.org/abstracts/search?q=Ukraine" title=" Ukraine"> Ukraine</a> </p> <a href="https://publications.waset.org/abstracts/169841/causality-between-stock-indices-and-cryptocurrencies-during-the-russia-ukraine-war" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/169841.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">67</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1051</span> Investigating the Relationship between the Kuwait Stock Market and Its Marketing Sectors</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Mohamad%20H.%20Atyeh">Mohamad H. Atyeh</a>, <a href="https://publications.waset.org/abstracts/search?q=Ahmad%20Khaldi"> Ahmad Khaldi</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The main objective of this research is to measure the relationship between the Kuwait stock Exchange (KSE) index and its two marketing sectors after the new market classification. The findings of this research are important for Public economic policy makers as they need to know if the new system (new classification) is efficient and to what level, to monitor the markets and intervene with appropriate measures. The data used are the daily index of the whole Kuwaiti market and the daily closing price, number of deals and volume of shares traded of two marketing sectors (consumer goods and consumer services) for the period from the 13th of May 2012 till the 12th of December 2016. The results indicate a positive direct impact of the closing price, volume and deals indexes of the consumer goods and the consumer services companies on the overall KSE index, volume and deals of the Kuwaiti stock market (KSE). <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=correlation" title="correlation">correlation</a>, <a href="https://publications.waset.org/abstracts/search?q=market%20capitalization" title=" market capitalization"> market capitalization</a>, <a href="https://publications.waset.org/abstracts/search?q=Kuwait%20Stock%20Exchange%20%28KSE%29" title=" Kuwait Stock Exchange (KSE)"> Kuwait Stock Exchange (KSE)</a>, <a href="https://publications.waset.org/abstracts/search?q=marketing%20sectors" title=" marketing sectors"> marketing sectors</a>, <a href="https://publications.waset.org/abstracts/search?q=stock%20performance" title=" stock performance"> stock performance</a> </p> <a href="https://publications.waset.org/abstracts/76744/investigating-the-relationship-between-the-kuwait-stock-market-and-its-marketing-sectors" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/76744.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">326</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1050</span> The Impact of the Global Financial Crises on MILA Stock Markets </h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Miriam%20Sosa">Miriam Sosa</a>, <a href="https://publications.waset.org/abstracts/search?q=Edgar%20Ortiz"> Edgar Ortiz</a>, <a href="https://publications.waset.org/abstracts/search?q=Alejandra%20Cabello"> Alejandra Cabello</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This paper examines the volatility changes and leverage effects of the MILA stock markets and their changes since the 2007 global financial crisis. This group integrates the stock markets from Chile, Colombia, Mexico and Peru. Volatility changes and leverage effects are tested with a symmetric GARCH (1,1) and asymmetric TARCH (1,1) models with a dummy variable in the variance equation. Daily closing prices of the stock indexes of Chile (IPSA), Colombia (COLCAP), Mexico (IPC) and Peru (IGBVL) are examined for the period 2003:01 to 2015:02. The evidence confirms the presence of an overall increase in asymmetric market volatility in the Peruvian share market since the 2007 crisis. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=financial%20crisis" title="financial crisis">financial crisis</a>, <a href="https://publications.waset.org/abstracts/search?q=Latin%20American%20Integrated%20Market" title=" Latin American Integrated Market"> Latin American Integrated Market</a>, <a href="https://publications.waset.org/abstracts/search?q=TARCH" title=" TARCH"> TARCH</a>, <a href="https://publications.waset.org/abstracts/search?q=GARCH" title=" GARCH"> GARCH</a> </p> <a href="https://publications.waset.org/abstracts/57884/the-impact-of-the-global-financial-crises-on-mila-stock-markets" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/57884.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">279</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1049</span> Value at Risk and Expected Shortfall of Firms in the Main European Union Stock Market Indexes: A Detailed Analysis by Economic Sectors and Geographical Situation</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Emma%20M.%20Iglesias">Emma M. Iglesias</a> </p> <p class="card-text"><strong>Abstract:</strong></p> We have analyzed extreme movements of the main stocks traded in the Eurozone in the 2000-2012 period. Our results can help future very-risk-averse investors to choose their portfolios in the Eurozone for risk management purposes. We find two main results. First, we can clearly classify firms by economic sector according to their different estimated VaR values in five of the seven countries we analyze. In special, we find sectors in general where companies have very high (telecommunications and banking) and very low (petroleum, utilities, energy and consumption) estimated VaR values. Second, we only find differences according to the geographical situation of where the stocks are traded in two countries: (1) all firms in the Irish stock market (the only financially rescued country we analyze) have very high estimated VaR values in all sectors; while (2) in Spain all firms have very low estimated VaR values including in the banking and the telecommunications sectors. All our results are supported when we study also the expected shortfall of the firms. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=risk%20management" title="risk management">risk management</a>, <a href="https://publications.waset.org/abstracts/search?q=firms" title=" firms"> firms</a>, <a href="https://publications.waset.org/abstracts/search?q=pareto%20tail%20thickness%20parameter" title=" pareto tail thickness parameter"> pareto tail thickness parameter</a>, <a href="https://publications.waset.org/abstracts/search?q=GARCH-type%20models" title=" GARCH-type models"> GARCH-type models</a>, <a href="https://publications.waset.org/abstracts/search?q=value-at-risk" title=" value-at-risk"> value-at-risk</a>, <a href="https://publications.waset.org/abstracts/search?q=extreme%20value%20theory" title=" extreme value theory"> extreme value theory</a>, <a href="https://publications.waset.org/abstracts/search?q=heavy%20tails" title=" heavy tails"> heavy tails</a>, <a href="https://publications.waset.org/abstracts/search?q=stock%20indexes" title=" stock indexes"> stock indexes</a>, <a href="https://publications.waset.org/abstracts/search?q=eurozone" title=" eurozone"> eurozone</a> </p> <a href="https://publications.waset.org/abstracts/15885/value-at-risk-and-expected-shortfall-of-firms-in-the-main-european-union-stock-market-indexes-a-detailed-analysis-by-economic-sectors-and-geographical-situation" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/15885.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">371</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1048</span> Mean Reversion in Stock Prices: Evidence from Karachi Stock Exchange</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Tabassum%20Riaz">Tabassum Riaz</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This study provides a complete examination of the stock prices behavior in the Karachi stock exchange. It examines that whether Karachi stock exchange can be described as mean reversion or not. For this purpose daily, weekly and monthly index data from Karachi stock exchange ranging from period July 1, 1997 to July 2, 2011 was taken. After employing the Multiple variance ratio and unit root tests it is concluded that stock market follow mean reversion behavior and hence have reverting trend which opens the door for the active invest management. Thus technical analysis may be help to identify the potential areas for value creation. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=mean%20reversion" title="mean reversion">mean reversion</a>, <a href="https://publications.waset.org/abstracts/search?q=random%20walk" title=" random walk"> random walk</a>, <a href="https://publications.waset.org/abstracts/search?q=technical%20analysis" title=" technical analysis"> technical analysis</a>, <a href="https://publications.waset.org/abstracts/search?q=Karachi%20stock%20exchange" title=" Karachi stock exchange"> Karachi stock exchange</a> </p> <a href="https://publications.waset.org/abstracts/23494/mean-reversion-in-stock-prices-evidence-from-karachi-stock-exchange" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/23494.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">432</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1047</span> Role of Cryptocurrency in Portfolio Diversification</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Onur%20Arugaslan">Onur Arugaslan</a>, <a href="https://publications.waset.org/abstracts/search?q=Ajay%20Samant"> Ajay Samant</a>, <a href="https://publications.waset.org/abstracts/search?q=Devrim%20Yaman"> Devrim Yaman</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Financial advisors and investors seek new assets which could potentially increase portfolio returns and decrease portfolio risk. Cryptocurrencies represent a relatively new asset class which could serve in both these roles. There has been very little research done in the area of the risk/return tradeoff in a portfolio consisting of fixed income assets, stocks, and cryptocurrency. The objective of this study is a rigorous examination of this issue. The data used in the study are the monthly returns on 4-week US Treasury Bills, S&P Investment Grade Corporate Bond Index, Bitcoin and the S&P 500 Stock Index. The methodology used in the study is the application Modern Portfolio Theory to evaluate the risk-adjusted returns of portfolios with varying combinations of these assets, using Sharpe, Treynor and Jensen Indexes, as well as the Sortino and Modigliani measures. The results of the study would include the ranking of various investment portfolios based on their risk/return characteristics. The conclusions of the study would include objective empirical inference for investors who are interested in including cryptocurrency in their asset portfolios but are unsure of the risk/return implications. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=financial%20economics" title="financial economics">financial economics</a>, <a href="https://publications.waset.org/abstracts/search?q=portfolio%20diversification" title=" portfolio diversification"> portfolio diversification</a>, <a href="https://publications.waset.org/abstracts/search?q=fixed%20income%20securities" title=" fixed income securities"> fixed income securities</a>, <a href="https://publications.waset.org/abstracts/search?q=cryptocurrency" title=" cryptocurrency"> cryptocurrency</a>, <a href="https://publications.waset.org/abstracts/search?q=stock%20indexes" title=" stock indexes"> stock indexes</a> </p> <a href="https://publications.waset.org/abstracts/173618/role-of-cryptocurrency-in-portfolio-diversification" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/173618.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">73</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1046</span> Estimating the Volatilite of Stock Markets in Case of Financial Crisis</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Gultekin%20Gurcay">Gultekin Gurcay</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this paper, effects and responses of stock were analyzed. This analysis was done periodically. The dimensions of the financial crisis impact on the stock market were investigated by GARCH model. In this context, S&P 500 stock market is modeled with DAX, NIKKEI and BIST100. In this way, The effects of the changing in S&P 500 stock market were examined on European and Asian stock markets. Conditional variance coefficient will be calculated through garch model. The scope of the crisis period, the conditional covariance coefficient will be analyzed comparatively. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=conditional%20variance%20coefficient" title="conditional variance coefficient">conditional variance coefficient</a>, <a href="https://publications.waset.org/abstracts/search?q=financial%20crisis" title=" financial crisis"> financial crisis</a>, <a href="https://publications.waset.org/abstracts/search?q=garch%20model" title=" garch model"> garch model</a>, <a href="https://publications.waset.org/abstracts/search?q=stock%20market" title=" stock market"> stock market</a> </p> <a href="https://publications.waset.org/abstracts/40843/estimating-the-volatilite-of-stock-markets-in-case-of-financial-crisis" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/40843.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">294</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1045</span> The Fefe Indices: The Direction of Donal Trump’s Tweets Effect on the Stock Market</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Sergio%20Andres%20Rojas">Sergio Andres Rojas</a>, <a href="https://publications.waset.org/abstracts/search?q=Julian%20Benavides%20Franco"> Julian Benavides Franco</a>, <a href="https://publications.waset.org/abstracts/search?q=Juan%20Tomas%20Sayago"> Juan Tomas Sayago</a> </p> <p class="card-text"><strong>Abstract:</strong></p> An increasing amount of research demonstrates how market mood affects financial markets, but their primary goal is to demonstrate how Trump's tweets impacted US interest rate volatility. Following that lead, this work evaluates the effect that Trump's tweets had during his presidency on local and international stock markets, considering not just volatility but the direction of the movement. Three indexes for Trump's tweets were created relating his activity with movements in the S&P500 using natural language analysis and machine learning algorithms. The indexes consider Trump's tweet activity and the positive or negative market sentiment they might inspire. The first explores the relationship between tweets generating negative movements in the S&P500; the second explores positive movements, while the third explores the difference between up and down movements. A pseudo-investment strategy using the indexes produced statistically significant above-average abnormal returns. The findings also showed that the pseudo strategy generated a higher return in the local market if applied to intraday data. However, only a negative market sentiment caused this effect on daily data. These results suggest that the market reacted primarily to a negative idea reflected in the negative index. In the international market, it is not possible to identify a pervasive effect. A rolling window regression model was also performed. The result shows that the impact on the local and international markets is heterogeneous, time-changing, and differentiated for the market sentiment. However, the negative sentiment was more prone to have a significant correlation most of the time. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=market%20sentiment" title="market sentiment">market sentiment</a>, <a href="https://publications.waset.org/abstracts/search?q=Twitter%20market%20sentiment" title=" Twitter market sentiment"> Twitter market sentiment</a>, <a href="https://publications.waset.org/abstracts/search?q=machine%20learning" title=" machine learning"> machine learning</a>, <a href="https://publications.waset.org/abstracts/search?q=natural%20dialect%20analysis" title=" natural dialect analysis"> natural dialect analysis</a> </p> <a href="https://publications.waset.org/abstracts/174703/the-fefe-indices-the-direction-of-donal-trumps-tweets-effect-on-the-stock-market" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/174703.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">63</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1044</span> A Case-Based Reasoning-Decision Tree Hybrid System for Stock Selection</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Yaojun%20Wang">Yaojun Wang</a>, <a href="https://publications.waset.org/abstracts/search?q=Yaoqing%20Wang"> Yaoqing Wang</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Stock selection is an important decision-making problem. Many machine learning and data mining technologies are employed to build automatic stock-selection system. A profitable stock-selection system should consider the stock’s investment value and the market timing. In this paper, we present a hybrid system including both engage for stock selection. This system uses a case-based reasoning (CBR) model to execute the stock classification, uses a decision-tree model to help with market timing and stock selection. The experiments show that the performance of this hybrid system is better than that of other techniques regarding to the classification accuracy, the average return and the Sharpe ratio. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=case-based%20reasoning" title="case-based reasoning">case-based reasoning</a>, <a href="https://publications.waset.org/abstracts/search?q=decision%20tree" title=" decision tree"> decision tree</a>, <a href="https://publications.waset.org/abstracts/search?q=stock%20selection" title=" stock selection"> stock selection</a>, <a href="https://publications.waset.org/abstracts/search?q=machine%20learning" title=" machine learning"> machine learning</a> </p> <a href="https://publications.waset.org/abstracts/48974/a-case-based-reasoning-decision-tree-hybrid-system-for-stock-selection" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/48974.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">420</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1043</span> Morphotectonic Analysis of Burkh Anticline, North of Bastak, Zagros</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=A.%20Afroogh">A. Afroogh</a>, <a href="https://publications.waset.org/abstracts/search?q=R.%20Ramazani%20omali"> R. Ramazani omali</a>, <a href="https://publications.waset.org/abstracts/search?q=N.%20Hafezi%20Moghaddas"> N. Hafezi Moghaddas</a>, <a href="https://publications.waset.org/abstracts/search?q=A.%20Nohegar"> A. Nohegar</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The Burkh anticline with a length of 50 km and a width of 9 km is located 40 km to the north of Bastak in internal Fars zone in folded-trusted belt of Zagros. In order to assess the active tectonics in the area of study, morphometrical indexes such as V indexes (V), ratio of valley floor to valley width (Vf), the stream length-gradient ratio (Sl), channel sinuosity indexes (S), mountain front faceting indexes (F%) and mountain front sinuosity(Smf) have been studied. These investigations show that the activity is not equal in various sections of the length of Burkh anticline. The central part of this anticline is the most active one. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=anticline" title="anticline">anticline</a>, <a href="https://publications.waset.org/abstracts/search?q=internal%20fars%20zone" title=" internal fars zone"> internal fars zone</a>, <a href="https://publications.waset.org/abstracts/search?q=tectonic" title=" tectonic"> tectonic</a>, <a href="https://publications.waset.org/abstracts/search?q=morohometrical%20indexes" title=" morohometrical indexes"> morohometrical indexes</a>, <a href="https://publications.waset.org/abstracts/search?q=folded-trusted%20belt" title=" folded-trusted belt"> folded-trusted belt</a> </p> <a href="https://publications.waset.org/abstracts/2278/morphotectonic-analysis-of-burkh-anticline-north-of-bastak-zagros" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/2278.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">250</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1042</span> Study of the Use of Artificial Neural Networks in Islamic Finance</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Kaoutar%20Abbahaddou">Kaoutar Abbahaddou</a>, <a href="https://publications.waset.org/abstracts/search?q=Mohammed%20Salah%20Chiadmi"> Mohammed Salah Chiadmi</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The need to find a relevant way to predict the next-day price of a stock index is a real concern for many financial stakeholders and researchers. We have known across years the proliferation of several methods. Nevertheless, among all these methods, the most controversial one is a machine learning algorithm that claims to be reliable, namely neural networks. Thus, the purpose of this article is to study the prediction power of neural networks in the particular case of Islamic finance as it is an under-looked area. In this article, we will first briefly present a review of the literature regarding neural networks and Islamic finance. Next, we present the architecture and principles of artificial neural networks most commonly used in finance. Then, we will show its empirical application on two Islamic stock indexes. The accuracy rate would be used to measure the performance of the algorithm in predicting the right price the next day. As a result, we can conclude that artificial neural networks are a reliable method to predict the next-day price for Islamic indices as it is claimed for conventional ones. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=Islamic%20finance" title="Islamic finance">Islamic finance</a>, <a href="https://publications.waset.org/abstracts/search?q=stock%20price%20prediction" title=" stock price prediction"> stock price prediction</a>, <a href="https://publications.waset.org/abstracts/search?q=artificial%20neural%20networks" title=" artificial neural networks"> artificial neural networks</a>, <a href="https://publications.waset.org/abstracts/search?q=machine%20learning" title=" machine learning"> machine learning</a> </p> <a href="https://publications.waset.org/abstracts/142047/study-of-the-use-of-artificial-neural-networks-in-islamic-finance" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/142047.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">237</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1041</span> A Network Approach to Analyzing Financial Markets</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Yusuf%20Seedat">Yusuf Seedat</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The necessity to understand global financial markets has increased following the unfortunate spread of the recent financial crisis around the world. Financial markets are considered to be complex systems consisting of highly volatile move-ments whose indexes fluctuate without any clear pattern. Analytic methods of stock prices have been proposed in which financial markets are modeled using common network analysis tools and methods. It has been found that two key components of social network analysis are relevant to modeling financial markets, allowing us to forecast accurate predictions of stock prices within the financial market. Financial markets have a number of interacting components, leading to complex behavioral patterns. This paper describes a social network approach to analyzing financial markets as a viable approach to studying the way complex stock markets function. We also look at how social network analysis techniques and metrics are used to gauge an understanding of the evolution of financial markets as well as how community detection can be used to qualify and quantify in-fluence within a network. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=network%20analysis" title="network analysis">network analysis</a>, <a href="https://publications.waset.org/abstracts/search?q=social%20networks" title=" social networks"> social networks</a>, <a href="https://publications.waset.org/abstracts/search?q=financial%20markets" title=" financial markets"> financial markets</a>, <a href="https://publications.waset.org/abstracts/search?q=stocks" title=" stocks"> stocks</a>, <a href="https://publications.waset.org/abstracts/search?q=nodes" title=" nodes"> nodes</a>, <a href="https://publications.waset.org/abstracts/search?q=edges" title=" edges"> edges</a>, <a href="https://publications.waset.org/abstracts/search?q=complex%20networks" title=" complex networks"> complex networks</a> </p> <a href="https://publications.waset.org/abstracts/142621/a-network-approach-to-analyzing-financial-markets" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/142621.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">191</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1040</span> Stock Price Prediction Using Time Series Algorithms</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Sumit%20Sen">Sumit Sen</a>, <a href="https://publications.waset.org/abstracts/search?q=Sohan%20Khedekar"> Sohan Khedekar</a>, <a href="https://publications.waset.org/abstracts/search?q=Umang%20Shinde"> Umang Shinde</a>, <a href="https://publications.waset.org/abstracts/search?q=Shivam%20Bhargava"> Shivam Bhargava</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This study has been undertaken to investigate whether the deep learning models are able to predict the future stock prices by training the model with the historical stock price data. Since this work required time series analysis, various models are present today to perform time series analysis such as Recurrent Neural Network LSTM, ARIMA and Facebook Prophet. Applying these models the movement of stock price of stocks are predicted and also tried to provide the future prediction of the stock price of a stock. Final product will be a stock price prediction web application that is developed for providing the user the ease of analysis of the stocks and will also provide the predicted stock price for the next seven days. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=Autoregressive%20Integrated%20Moving%20Average" title="Autoregressive Integrated Moving Average">Autoregressive Integrated Moving Average</a>, <a href="https://publications.waset.org/abstracts/search?q=Deep%20Learning" title=" Deep Learning"> Deep Learning</a>, <a href="https://publications.waset.org/abstracts/search?q=Long%20Short%20Term%20Memory" title=" Long Short Term Memory"> Long Short Term Memory</a>, <a href="https://publications.waset.org/abstracts/search?q=Time-series" title=" Time-series"> Time-series</a> </p> <a href="https://publications.waset.org/abstracts/137402/stock-price-prediction-using-time-series-algorithms" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/137402.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">141</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1039</span> Firm Performance and Stock Price in Nigeria</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Tijjani%20Bashir%20Musa">Tijjani Bashir Musa</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The recent global crisis which suddenly results to Nigerian stock market crash revealed some peculiarities of Nigerian firms. Some firms in Nigeria are performing but their stock prices are not increasing while some firms are at the brink of collapse but their stock prices are increasing. Thus, this study examines the relationship between firm performance and stock price in Nigeria. The study covered the period of 2005 to 2009. This period is the period of stock boom and also marked the period of stock market crash as a result of global financial meltdown. The study is a panel study. A total of 140 firms were sampled from 216 firms listed on the Nigerian Stock Exchange (NSE). Data were collected from secondary source. These data were divided into four strata comprising the most performing stock, the least performing stock, most performing firms and the least performing firms. Each stratum contains 35 firms with characteristic of most performing stock, most performing firms, least performing stock and least performing firms. Multiple linear regression models were used to analyse the data while statistical/econometrics package of Stata 11.0 version was used to run the data. The study found that, relationship exists between selected firm performance parameters (operating efficiency, firm profit, earning per share and working capital) and stock price. As such firm performance gave sufficient information or has predictive power on stock prices movements in Nigeria for all the years under study.. The study recommends among others that Managers of firms in Nigeria should formulate policies and exert effort geared towards improving firm performance that will enhance stock prices movements. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=firm" title="firm">firm</a>, <a href="https://publications.waset.org/abstracts/search?q=Nigeria" title=" Nigeria"> Nigeria</a>, <a href="https://publications.waset.org/abstracts/search?q=performance" title=" performance"> performance</a>, <a href="https://publications.waset.org/abstracts/search?q=stock%20price" title=" stock price"> stock price</a> </p> <a href="https://publications.waset.org/abstracts/27645/firm-performance-and-stock-price-in-nigeria" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/27645.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">475</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1038</span> A Stock Exchange Analysis in Turkish Logistics Sector: Modeling, Forecasting, and Comparison with Logistics Indices </h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Eti%20Mizrahi">Eti Mizrahi</a>, <a href="https://publications.waset.org/abstracts/search?q=Gizem%20%C4%B0ntepe"> Gizem İntepe</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The geographical location of Turkey that stretches from Asia to Europe and Russia to Africa makes it an important logistics hub in the region. Although logistics is a developing sector in Turkey, the stock market representation is still low with only two companies listed in Turkey’s stock exchange since 2010. In this paper, we use the daily values of these two listed stocks as a benchmark for the logistics sector. After modeling logistics stock prices, an empirical examination is conducted between the existing logistics indices and these stock prices. The paper investigates whether the measures of logistics stocks are correlated with newly available logistics indices. It also shows the reflection of the economic activity in the logistics sector on the stock exchange market. The results presented in this paper are the first analysis of the behavior of logistics indices and logistics stock prices for Turkey. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=forecasting" title="forecasting">forecasting</a>, <a href="https://publications.waset.org/abstracts/search?q=logistic%20stock%20exchange" title=" logistic stock exchange"> logistic stock exchange</a>, <a href="https://publications.waset.org/abstracts/search?q=modeling" title=" modeling"> modeling</a>, <a href="https://publications.waset.org/abstracts/search?q=Africa" title=" Africa "> Africa </a> </p> <a href="https://publications.waset.org/abstracts/15459/a-stock-exchange-analysis-in-turkish-logistics-sector-modeling-forecasting-and-comparison-with-logistics-indices" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/15459.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">541</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1037</span> Value Relevance of Accounting Information: Empirical Evidence from China</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Ying%20Guo">Ying Guo</a>, <a href="https://publications.waset.org/abstracts/search?q=Miaochan%20Li"> Miaochan Li</a>, <a href="https://publications.waset.org/abstracts/search?q=David%20Yang"> David Yang</a>, <a href="https://publications.waset.org/abstracts/search?q=Xiao-Yan%20Li"> Xiao-Yan Li</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This paper examines the relevance of accounting information to stock prices at different periods using manufacturing companies listed in China’s Growth Enterprise Market (GEM). We find that both the average stock price at fiscal year-end and the average stock price one month after fiscal year-end are more relevant to the accounting information than the closing stock price four months after fiscal year-end. This implies that Chinese stock markets react before the public disclosure of accounting information, which may be due to information leak before official announcements. Our findings confirm that accounting information is relevant to stock prices for Chinese listed manufacturing companies, which is a critical question to answer for investors who have interest in Chinese companies. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=accounting%20information" title="accounting information">accounting information</a>, <a href="https://publications.waset.org/abstracts/search?q=response%20time" title=" response time"> response time</a>, <a href="https://publications.waset.org/abstracts/search?q=value%20relevance" title=" value relevance"> value relevance</a>, <a href="https://publications.waset.org/abstracts/search?q=stock%20price" title=" stock price"> stock price</a> </p> <a href="https://publications.waset.org/abstracts/165552/value-relevance-of-accounting-information-empirical-evidence-from-china" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/165552.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">96</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1036</span> Stock Movement Prediction Using Price Factor and Deep Learning</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Hy%20Dang">Hy Dang</a>, <a href="https://publications.waset.org/abstracts/search?q=Bo%20Mei"> Bo Mei</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The development of machine learning methods and techniques has opened doors for investigation in many areas such as medicines, economics, finance, etc. One active research area involving machine learning is stock market prediction. This research paper tries to consider multiple techniques and methods for stock movement prediction using historical price or price factors. The paper explores the effectiveness of some deep learning frameworks for forecasting stock. Moreover, an architecture (TimeStock) is proposed which takes the representation of time into account apart from the price information itself. Our model achieves a promising result that shows a potential approach for the stock movement prediction problem. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=classification" title="classification">classification</a>, <a href="https://publications.waset.org/abstracts/search?q=machine%20learning" title=" machine learning"> machine learning</a>, <a href="https://publications.waset.org/abstracts/search?q=time%20representation" title=" time representation"> time representation</a>, <a href="https://publications.waset.org/abstracts/search?q=stock%20prediction" title=" stock prediction"> stock prediction</a> </p> <a href="https://publications.waset.org/abstracts/147469/stock-movement-prediction-using-price-factor-and-deep-learning" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/147469.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">147</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1035</span> Does Level of Countries Corruption Affect Firms Working Capital Management? </h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Ebrahim%20Mansoori">Ebrahim Mansoori</a>, <a href="https://publications.waset.org/abstracts/search?q=Datin%20Joriah%20Muhammad"> Datin Joriah Muhammad </a> </p> <p class="card-text"><strong>Abstract:</strong></p> Recent studies in finance have focused on the effect of external variables on working capital management. This study investigates the effect of corruption indexes on firms' working capital management. A large data set that covers data from 2005 to 2013 from five ASEAN countries, namely, Malaysia, Indonesia, Singapore, Thailand, and the Philippines, was selected to investigate how the level of corruption in these countries affect working capital management. The results of panel data analysis include fixed effect estimations showed that a high level of countries' corruption indexes encourages managers to shorten the CCC length. Meanwhile, the managers reduce the level of investment in cash and cash equivalents when the levels of corruption indexes increase. Therefore, increasing the level of countries' corruption indexes encourages managers to select conservative working capital strategies by reducing the level of NLB. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=ASEAN" title="ASEAN">ASEAN</a>, <a href="https://publications.waset.org/abstracts/search?q=corruption%20indexes" title=" corruption indexes"> corruption indexes</a>, <a href="https://publications.waset.org/abstracts/search?q=panel%20data%20analysis" title=" panel data analysis"> panel data analysis</a>, <a href="https://publications.waset.org/abstracts/search?q=working%20capital%20management" title=" working capital management "> working capital management </a> </p> <a href="https://publications.waset.org/abstracts/20352/does-level-of-countries-corruption-affect-firms-working-capital-management" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/20352.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">438</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1034</span> Determination of Relationship among Shape Indexes Used for Land Consolidation</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Firat%20Arslan">Firat Arslan</a>, <a href="https://publications.waset.org/abstracts/search?q=Hasan%20Degirmenci"> Hasan Degirmenci</a>, <a href="https://publications.waset.org/abstracts/search?q=Serife%20Tulin%20Akkaya%20Aslan"> Serife Tulin Akkaya Aslan</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The aim of the current experiment was to determine the relationship among shape indexes which are used by the researchers in many fields to evaluate parcel shapes which is very important for farming even if these indexes are controversial. In the current study, land consolidation project of Halitaga village in Mersin province in Turkey which has 278 parcel and cover 894.4 ha, was taken as a material. Commonly used indicators such as fractal dimension (FD), shape index (SI), form factor (FORM), areal form factor (AFF) and two distinct area-perimeter ratio (APR-1 and APR2) in land consolidation are used to measure agricultural plot’s shape. FD was positively correlated with SI, APR-1 and APR-2 whereas it was negatively correlated with FORM and AFF. SI was positively correlated with APR-1 and APR-2 whereas it was negatively correlated with FORM and AFF. As a conclusion, it is likely that these indexes involved may be used interchangeably due to high correlations among them. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=GIS" title="GIS">GIS</a>, <a href="https://publications.waset.org/abstracts/search?q=land%20consolidation" title=" land consolidation"> land consolidation</a>, <a href="https://publications.waset.org/abstracts/search?q=parcel%20shape" title=" parcel shape"> parcel shape</a>, <a href="https://publications.waset.org/abstracts/search?q=shape%20index" title=" shape index"> shape index</a> </p> <a href="https://publications.waset.org/abstracts/89511/determination-of-relationship-among-shape-indexes-used-for-land-consolidation" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/89511.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">187</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1033</span> An Automated Stock Investment System Using Machine Learning Techniques: An Application in Australia</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Carol%20Anne%20Hargreaves">Carol Anne Hargreaves</a> </p> <p class="card-text"><strong>Abstract:</strong></p> A key issue in stock investment is how to select representative features for stock selection. The objective of this paper is to firstly determine whether an automated stock investment system, using machine learning techniques, may be used to identify a portfolio of growth stocks that are highly likely to provide returns better than the stock market index. The second objective is to identify the technical features that best characterize whether a stock’s price is likely to go up and to identify the most important factors and their contribution to predicting the likelihood of the stock price going up. Unsupervised machine learning techniques, such as cluster analysis, were applied to the stock data to identify a cluster of stocks that was likely to go up in price – portfolio 1. Next, the principal component analysis technique was used to select stocks that were rated high on component one and component two – portfolio 2. Thirdly, a supervised machine learning technique, the logistic regression method, was used to select stocks with a high probability of their price going up – portfolio 3. The predictive models were validated with metrics such as, sensitivity (recall), specificity and overall accuracy for all models. All accuracy measures were above 70%. All portfolios outperformed the market by more than eight times. The top three stocks were selected for each of the three stock portfolios and traded in the market for one month. After one month the return for each stock portfolio was computed and compared with the stock market index returns. The returns for all three stock portfolios was 23.87% for the principal component analysis stock portfolio, 11.65% for the logistic regression portfolio and 8.88% for the K-means cluster portfolio while the stock market performance was 0.38%. This study confirms that an automated stock investment system using machine learning techniques can identify top performing stock portfolios that outperform the stock market. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=machine%20learning" title="machine learning">machine learning</a>, <a href="https://publications.waset.org/abstracts/search?q=stock%20market%20trading" title=" stock market trading"> stock market trading</a>, <a href="https://publications.waset.org/abstracts/search?q=logistic%20regression" title=" logistic regression"> logistic regression</a>, <a href="https://publications.waset.org/abstracts/search?q=cluster%20analysis" title=" cluster analysis"> cluster analysis</a>, <a href="https://publications.waset.org/abstracts/search?q=factor%20analysis" title=" factor analysis"> factor analysis</a>, <a href="https://publications.waset.org/abstracts/search?q=decision%20trees" title=" decision trees"> decision trees</a>, <a href="https://publications.waset.org/abstracts/search?q=neural%20networks" title=" neural networks"> neural networks</a>, <a href="https://publications.waset.org/abstracts/search?q=automated%20stock%20investment%20system" title=" automated stock investment system"> automated stock investment system</a> </p> <a href="https://publications.waset.org/abstracts/90984/an-automated-stock-investment-system-using-machine-learning-techniques-an-application-in-australia" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/90984.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">157</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1032</span> Evaluating The Effects of Fundamental Analysis on Earnings Per Share Concept in Stock Valuation in the Zimbabwe Stock Exchange Market</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Brian%20Basvi">Brian Basvi</a> </p> <p class="card-text"><strong>Abstract:</strong></p> A technique for analyzing a security's intrinsic value is called fundamental analysis. It involves looking at relevant financial, economic, and other qualitative and quantitative aspects. Earnings Per Share (EPS), a crucial metric in fundamental analysis, is calculated by dividing a company's net income by the total number of outstanding shares. With more than 70 listed businesses, the Zimbabwe Stock Exchange (ZSE) is the primary stock exchange in Zimbabwe. This study applies the EPS financial ratio and stock valuation techniques to historical stock data from 68 companies listed on the Zimbabwe Stock Exchange. According to a ZSE study, EPS significantly affects share prices that are listed on the market. The study's objective was to assess how fundamental analysis affected the idea of EPS in ZSE stock valuation. It concluded that EPS is an important consideration for investors when they make judgments about their investments. According to the study's findings, fundamental analysis is a useful tool for ZSE investors since it offers insightful information about a company's financial performance and aids in decision-making. Investors can have a better understanding of a company's underlying worth and prospects for future growth by looking into EPS and other basic aspects. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=fundamental%20analysis" title="fundamental analysis">fundamental analysis</a>, <a href="https://publications.waset.org/abstracts/search?q=stock%20valuation" title=" stock valuation"> stock valuation</a>, <a href="https://publications.waset.org/abstracts/search?q=EPS" title=" EPS"> EPS</a>, <a href="https://publications.waset.org/abstracts/search?q=share%20pricing" title=" share pricing"> share pricing</a> </p> <a href="https://publications.waset.org/abstracts/188656/evaluating-the-effects-of-fundamental-analysis-on-earnings-per-share-concept-in-stock-valuation-in-the-zimbabwe-stock-exchange-market" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/188656.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">43</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1031</span> Using Deep Learning Neural Networks and Candlestick Chart Representation to Predict Stock Market</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Rosdyana%20Mangir%20Irawan%20Kusuma">Rosdyana Mangir Irawan Kusuma</a>, <a href="https://publications.waset.org/abstracts/search?q=Wei-Chun%20Kao"> Wei-Chun Kao</a>, <a href="https://publications.waset.org/abstracts/search?q=Ho-Thi%20Trang"> Ho-Thi Trang</a>, <a href="https://publications.waset.org/abstracts/search?q=Yu-Yen%20Ou"> Yu-Yen Ou</a>, <a href="https://publications.waset.org/abstracts/search?q=Kai-Lung%20Hua"> Kai-Lung Hua</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Stock market prediction is still a challenging problem because there are many factors that affect the stock market price such as company news and performance, industry performance, investor sentiment, social media sentiment, and economic factors. This work explores the predictability in the stock market using deep convolutional network and candlestick charts. The outcome is utilized to design a decision support framework that can be used by traders to provide suggested indications of future stock price direction. We perform this work using various types of neural networks like convolutional neural network, residual network and visual geometry group network. From stock market historical data, we converted it to candlestick charts. Finally, these candlestick charts will be feed as input for training a convolutional neural network model. This convolutional neural network model will help us to analyze the patterns inside the candlestick chart and predict the future movements of the stock market. The effectiveness of our method is evaluated in stock market prediction with promising results; 92.2% and 92.1 % accuracy for Taiwan and Indonesian stock market dataset respectively. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=candlestick%20chart" title="candlestick chart">candlestick chart</a>, <a href="https://publications.waset.org/abstracts/search?q=deep%20learning" title=" deep learning"> deep learning</a>, <a href="https://publications.waset.org/abstracts/search?q=neural%20network" title=" neural network"> neural network</a>, <a href="https://publications.waset.org/abstracts/search?q=stock%20market%20prediction" title=" stock market prediction"> stock market prediction</a> </p> <a href="https://publications.waset.org/abstracts/98615/using-deep-learning-neural-networks-and-candlestick-chart-representation-to-predict-stock-market" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/98615.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">447</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1030</span> Analyzing the Impact of Global Financial Crisis on Interconnectedness of Asian Stock Markets Using Network Science</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Jitendra%20Aswani">Jitendra Aswani</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In the first section of this study, impact of Global Financial Crisis (GFC) on the synchronization of fourteen Asian Stock Markets (ASM’s) of countries like Hong Kong, India, Thailand, Singapore, Taiwan, Pakistan, Bangladesh, South Korea, Malaysia, Indonesia, Japan, China, Philippines and Sri Lanka, has been analysed using the network science and its metrics like degree of node, clustering coefficient and network density. Then in the second section of this study by introducing the US stock market in existing network and developing a Minimum Spanning Tree (MST) spread of crisis from the US stock market to Asian Stock Markets (ASM) has been explained. Data used for this study is adjusted the closing price of these indices from 6th January, 2000 to 15th September, 2013 which further divided into three sub-periods: Pre, during and post-crisis. Using network analysis, it is found that Asian stock markets become more interdependent during the crisis than pre and post crisis, and also Hong Kong, India, South Korea and Japan are systemic important stock markets in the Asian region. Therefore, failure or shock to any of these systemic important stock markets can cause contagion to another stock market of this region. This study is useful for global investors’ in portfolio management especially during the crisis period and also for policy makers in formulating the financial regulation norms by knowing the connections between the stock markets and how the system of these stock markets changes in crisis period and after that. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=global%20financial%20crisis" title="global financial crisis">global financial crisis</a>, <a href="https://publications.waset.org/abstracts/search?q=Asian%20stock%20markets" title=" Asian stock markets"> Asian stock markets</a>, <a href="https://publications.waset.org/abstracts/search?q=network%20science" title=" network science"> network science</a>, <a href="https://publications.waset.org/abstracts/search?q=Kruskal%20algorithm" title=" Kruskal algorithm"> Kruskal algorithm</a> </p> <a href="https://publications.waset.org/abstracts/31876/analyzing-the-impact-of-global-financial-crisis-on-interconnectedness-of-asian-stock-markets-using-network-science" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/31876.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">424</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1029</span> The Shannon Entropy and Multifractional Markets</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Massimiliano%20Frezza">Massimiliano Frezza</a>, <a href="https://publications.waset.org/abstracts/search?q=Sergio%20Bianchi"> Sergio Bianchi</a>, <a href="https://publications.waset.org/abstracts/search?q=Augusto%20Pianese"> Augusto Pianese</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Introduced by Shannon in 1948 in the field of information theory as the average rate at which information is produced by a stochastic set of data, the concept of entropy has gained much attention as a measure of uncertainty and unpredictability associated with a dynamical system, eventually depicted by a stochastic process. In particular, the Shannon entropy measures the degree of order/disorder of a given signal and provides useful information about the underlying dynamical process. It has found widespread application in a variety of fields, such as, for example, cryptography, statistical physics and finance. In this regard, many contributions have employed different measures of entropy in an attempt to characterize the financial time series in terms of market efficiency, market crashes and/or financial crises. The Shannon entropy has also been considered as a measure of the risk of a portfolio or as a tool in asset pricing. This work investigates the theoretical link between the Shannon entropy and the multifractional Brownian motion (mBm), stochastic process which recently is the focus of a renewed interest in finance as a driving model of stochastic volatility. In particular, after exploring the current state of research in this area and highlighting some of the key results and open questions that remain, we show a well-defined relationship between the Shannon (log)entropy and the memory function H(t) of the mBm. In details, we allow both the length of time series and time scale to change over analysis to study how the relation modify itself. On the one hand, applications are developed after generating surrogates of mBm trajectories based on different memory functions; on the other hand, an empirical analysis of several international stock indexes, which confirms the previous results, concludes the work. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=Shannon%20entropy" title="Shannon entropy">Shannon entropy</a>, <a href="https://publications.waset.org/abstracts/search?q=multifractional%20Brownian%20motion" title=" multifractional Brownian motion"> multifractional Brownian motion</a>, <a href="https://publications.waset.org/abstracts/search?q=Hurst%E2%80%93Holder%20exponent" title=" Hurst–Holder exponent"> Hurst–Holder exponent</a>, <a href="https://publications.waset.org/abstracts/search?q=stock%20indexes" title=" stock indexes"> stock indexes</a> </p> <a href="https://publications.waset.org/abstracts/166023/the-shannon-entropy-and-multifractional-markets" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/166023.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">110</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1028</span> Application of Benford's Law in Analysis of Frankfurt Stock Exchange Index (DAX) Percentage Changes</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Mario%20Zgela">Mario Zgela</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Application of Benford’s Law is very rarely covered in the field of stock market analysis, especially in percentage change of stock market indices. Deutscher Aktien IndeX (DAX) is very important stock market index of Frankfurt Deutsche Börse which serves as underlying basis for large number of financial instruments. It is calculated for selected 30 German blue chips stocks. In this paper, Benford's Law first digit test is applied on 10 year DAX daily percentage changes in order to check compliance. Deviations of 10 year DAX percentage changes set as well as distortions of certain subsets from Benford's Law distribution are detected. It is possible that deviations are the outcome of speculations; and psychological influence should not be eliminated. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=Benford%27s%20Law" title="Benford's Law">Benford's Law</a>, <a href="https://publications.waset.org/abstracts/search?q=DAX" title=" DAX"> DAX</a>, <a href="https://publications.waset.org/abstracts/search?q=index%20percentage%20changes" title=" index percentage changes"> index percentage changes</a>, <a href="https://publications.waset.org/abstracts/search?q=stock%20market" title=" stock market"> stock market</a> </p> <a href="https://publications.waset.org/abstracts/2313/application-of-benfords-law-in-analysis-of-frankfurt-stock-exchange-index-dax-percentage-changes" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/2313.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">292</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1027</span> Volatility Transmission between Oil Price and Stock Return of Emerging and Developed Countries</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Algia%20Hammami">Algia Hammami</a>, <a href="https://publications.waset.org/abstracts/search?q=Abdelfatteh%20Bouri"> Abdelfatteh Bouri</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this work, our objective is to study the transmission of volatility between oil and stock markets in developed (USA, Germany, Italy, France and Japan) and emerging countries (Tunisia, Thailand, Brazil, Argentina, and Jordan) for the period 1998-2015. Our methodology consists of analyzing the monthly data by the GARCH-BEKK model to capture the effect in terms of volatility in the variation of the oil price on the different stock market. The empirical results in the emerging countries indicate that the relationships are unidirectional from the stock market to the oil market. For the developed countries, we find that the transmission of volatility is unidirectional from the oil market to stock market. For the USA and Italy, we find no transmission between the two markets. The transmission is bi-directional only in Thailand. Following our estimates, we also noticed that the emerging countries influence almost the same extent as the developed countries, while at the transmission of volatility there a bid difference. The GARCH-BEKK model is more effective than the others versions to minimize the risk of an oil-stock portfolio. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=GARCH" title="GARCH">GARCH</a>, <a href="https://publications.waset.org/abstracts/search?q=oil%20prices" title=" oil prices"> oil prices</a>, <a href="https://publications.waset.org/abstracts/search?q=stock%20market" title=" stock market"> stock market</a>, <a href="https://publications.waset.org/abstracts/search?q=volatility%20transmission" title=" volatility transmission"> volatility transmission</a> </p> <a href="https://publications.waset.org/abstracts/64379/volatility-transmission-between-oil-price-and-stock-return-of-emerging-and-developed-countries" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/64379.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">437</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1026</span> The Effect of the Enterprises Being Classified as Socially Responsible on Their Stock Returns</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Chih-Hsiang%20Chang">Chih-Hsiang Chang</a>, <a href="https://publications.waset.org/abstracts/search?q=Chia-Ching%20Tsai"> Chia-Ching Tsai</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The aim of this study is to examine the stock price effect of the enterprises being classified as socially responsible. We explore the stock price response to the announcement that an enterprise is selected for the Taiwan Corporate Sustainability Awards. Empirical results indicate that the announcements of the Taiwan Corporate Sustainability Awards provide useful informational content to stock market. We find the evidence of insignificantly positive short-term and significantly positive long-term price reaction to the enterprises being classified as socially responsible. This study concludes that investors in the Taiwan stock market tend to view an enterprise being selected for the Taiwan Corporate Sustainability Awards as one with superior quality and long-term price potential. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=corporate%20social%20responsibility" title="corporate social responsibility">corporate social responsibility</a>, <a href="https://publications.waset.org/abstracts/search?q=stock%20price%20effect" title=" stock price effect"> stock price effect</a>, <a href="https://publications.waset.org/abstracts/search?q=Taiwan%20stock%20market" title=" Taiwan stock market"> Taiwan stock market</a>, <a href="https://publications.waset.org/abstracts/search?q=investments" title=" investments"> investments</a> </p> <a href="https://publications.waset.org/abstracts/97842/the-effect-of-the-enterprises-being-classified-as-socially-responsible-on-their-stock-returns" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/97842.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">154</span> </span> </div> </div> <ul class="pagination"> <li class="page-item disabled"><span class="page-link">&lsaquo;</span></li> <li class="page-item active"><span class="page-link">1</span></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=stock%20indexes&page=2">2</a></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=stock%20indexes&page=3">3</a></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=stock%20indexes&page=4">4</a></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=stock%20indexes&page=5">5</a></li> <li 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