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weighted average price</title> <meta name="description" content="Search results for: volume weighted average price"> <meta name="keywords" content="volume weighted average price"> <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> 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action="https://publications.waset.org/abstracts/search"> <div 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="volume weighted average price"> <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> 8578</div> </div> </div> </div> <h1 class="mt-3 mb-3 text-center" style="font-size:1.6rem;">Search results for: volume weighted average price</h1> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">8578</span> Legal Thresholds in Germany Take Over: The Role of Minimum Offer Price Regulation</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Osei%20Kwabena%20Brefo">Osei Kwabena Brefo</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The Germany takeover regulations mandate the minimum offer price to be set in accordance with section 31 (1) of the WpÜG. To safeguard this right of the shareholders, the WpÜG contains minimum price regulations that are based on the fundamental principle of equal treatment of shareholders. The minimum offer price is determined based on the maximum of either the highest price the bidder has offered other shareholders within the last six months (§ 4 WpÜG) or the three-month weighted average stock price (§ 5 Abs. 1 WpÜG) before the announcement of the offer. This study provides the first empirical evidence on differences between setting the minimum offer price based on the highest price paid to another shareholder within the last six months (“6MH offers”) as against the three-month weighted average stock before the announcement of the offer (“VWAP offers”) in terms of their impact on acquisition outcome. Using a sample of 358 acquisitions announced between 2004 and 2023, the study finds that the market and legal minimum premium in 6MH offers are significantly lower than three-month weighted average stock price offers. The study also employed Propensity Score Matching and endogenous Linear regression model to address for endogeneity concerns. Consistent with the Ordinary Least Square estimation, the study finds that after controlling for self-selection bias, market and legal premiums in 6MH offers are significantly lower than VWAP offers. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=mergers%20and%20acquisition" title="mergers and acquisition">mergers and acquisition</a>, <a href="https://publications.waset.org/abstracts/search?q=offer%20premium" title=" offer premium"> offer premium</a>, <a href="https://publications.waset.org/abstracts/search?q=minimum%20price%20regulation" title=" minimum price regulation"> minimum price regulation</a>, <a href="https://publications.waset.org/abstracts/search?q=takeover%20regulation" title=" takeover regulation"> takeover regulation</a> </p> <a href="https://publications.waset.org/abstracts/195939/legal-thresholds-in-germany-take-over-the-role-of-minimum-offer-price-regulation" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/195939.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">13</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">8577</span> A Data Science Pipeline for Algorithmic Trading: A Comparative Study in Applications to Finance and Cryptoeconomics</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Luyao%20Zhang">Luyao Zhang</a>, <a href="https://publications.waset.org/abstracts/search?q=Tianyu%20Wu"> Tianyu Wu</a>, <a href="https://publications.waset.org/abstracts/search?q=Jiayi%20Li"> Jiayi Li</a>, <a href="https://publications.waset.org/abstracts/search?q=Carlos-Gustavo%20Salas-Flores"> Carlos-Gustavo Salas-Flores</a>, <a href="https://publications.waset.org/abstracts/search?q=Saad%20Lahrichi"> Saad Lahrichi</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Recent advances in AI have made algorithmic trading a central role in finance. However, current research and applications are disconnected information islands. We propose a generally applicable pipeline for designing, programming, and evaluating algorithmic trading of stock and crypto tokens. Moreover, we provide comparative case studies for four conventional algorithms, including moving average crossover, volume-weighted average price, sentiment analysis, and statistical arbitrage. Our study offers a systematic way to program and compare different trading strategies. Moreover, we implement our algorithms by object-oriented programming in Python3, which serves as open-source software for future academic research and applications. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=algorithmic%20trading" title="algorithmic trading">algorithmic trading</a>, <a href="https://publications.waset.org/abstracts/search?q=AI%20for%20finance" title=" AI for finance"> AI for finance</a>, <a href="https://publications.waset.org/abstracts/search?q=fintech" title=" fintech"> fintech</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=moving%20average%20crossover" title=" moving average crossover"> moving average crossover</a>, <a href="https://publications.waset.org/abstracts/search?q=volume%20weighted%20average%20price" title=" volume weighted average price"> volume weighted average price</a>, <a href="https://publications.waset.org/abstracts/search?q=sentiment%20analysis" title=" sentiment analysis"> sentiment analysis</a>, <a href="https://publications.waset.org/abstracts/search?q=statistical%20arbitrage" title=" statistical arbitrage"> statistical arbitrage</a>, <a href="https://publications.waset.org/abstracts/search?q=pair%20trading" title=" pair trading"> pair trading</a>, <a href="https://publications.waset.org/abstracts/search?q=object-oriented%20programming" title=" object-oriented programming"> object-oriented programming</a>, <a href="https://publications.waset.org/abstracts/search?q=python3" title=" python3"> python3</a> </p> <a href="https://publications.waset.org/abstracts/146823/a-data-science-pipeline-for-algorithmic-trading-a-comparative-study-in-applications-to-finance-and-cryptoeconomics" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/146823.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">149</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">8576</span> Analysis of Spatial Heterogeneity of Residential Prices in Guangzhou: An Actual Study Based on Point of Interest Geographically Weighted Regression Model</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Zichun%20Guo">Zichun Guo</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Guangzhou's house price has long been lower than the other three major cities; with the gradual increase in Guangzhou's house price, the influencing factors of house price have gradually been paid attention to; this paper tries to use house price data and POI (Point of Interest) data, and explores the distribution of house price and influencing factors by applying the Kriging spatial interpolation method and geographically weighted regression model in ArcGIS. The results show that the interpolation result of house price has a significant relationship with the economic development and development potential of the region and that different POI types have different impacts on the growth of house prices in different regions. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=POI" title="POI">POI</a>, <a href="https://publications.waset.org/abstracts/search?q=house%20price" title=" house price"> house price</a>, <a href="https://publications.waset.org/abstracts/search?q=spatial%20heterogeneity" title=" spatial heterogeneity"> spatial heterogeneity</a>, <a href="https://publications.waset.org/abstracts/search?q=Guangzhou" title=" Guangzhou"> Guangzhou</a> </p> <a href="https://publications.waset.org/abstracts/185907/analysis-of-spatial-heterogeneity-of-residential-prices-in-guangzhou-an-actual-study-based-on-point-of-interest-geographically-weighted-regression-model" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/185907.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">58</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">8575</span> The Carbon Trading Price and Trading Volume Forecast in Shanghai City by BP Neural Network</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Liu%20Zhiyuan">Liu Zhiyuan</a>, <a href="https://publications.waset.org/abstracts/search?q=Sun%20Zongdi"> Sun Zongdi</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this paper, the BP neural network model is established to predict the carbon trading price and carbon trading volume in Shanghai City. First of all, we find the data of carbon trading price and carbon trading volume in Shanghai City from September 30, 2015 to December 23, 2016. The carbon trading price and trading volume data were processed to get the average value of each 5, 10, 20, 30, and 60 carbon trading price and trading volume. Then, these data are used as input of BP neural network model. Finally, after the training of BP neural network, the prediction values of Shanghai carbon trading price and trading volume are obtained, and the model is tested. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=Carbon%20trading%20price" title="Carbon trading price">Carbon trading price</a>, <a href="https://publications.waset.org/abstracts/search?q=carbon%20trading%20volume" title=" carbon trading volume"> carbon trading volume</a>, <a href="https://publications.waset.org/abstracts/search?q=BP%20neural%20network%20model" title=" BP neural network model"> BP neural network model</a>, <a href="https://publications.waset.org/abstracts/search?q=Shanghai%20City" title=" Shanghai City"> Shanghai City</a> </p> <a href="https://publications.waset.org/abstracts/69753/the-carbon-trading-price-and-trading-volume-forecast-in-shanghai-city-by-bp-neural-network" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/69753.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">353</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">8574</span> A Comparative Analysis of Grade Weighted Average and Comprehensive Examination Result of Non Board Passers and Board Passers</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Rob%20Gesley%20Capistrano">Rob Gesley Capistrano</a>, <a href="https://publications.waset.org/abstracts/search?q=Jasper%20James%20Isaac"> Jasper James Isaac</a>, <a href="https://publications.waset.org/abstracts/search?q=Rose%20Mae%20Moralda"> Rose Mae Moralda</a>, <a href="https://publications.waset.org/abstracts/search?q=Therese%20Anne%20Peleo"> Therese Anne Peleo</a>, <a href="https://publications.waset.org/abstracts/search?q=Danica%20Rillo"> Danica Rillo</a>, <a href="https://publications.waset.org/abstracts/search?q=Maria%20Virginia%20Santillian"> Maria Virginia Santillian</a> </p> <p class="card-text"><strong>Abstract:</strong></p> One of the valuable things that shows the intelligence among individuals is the academic background specifically their Grade Weighted Average and the significant result of the Comprehensive Examination. The general objective of the researchers to this study is to determine if there is a significant difference between General Weighted Average and Comprehensive Examination Result of Psychometrician Board Passers and Non-Board Passers. The respondents of this study composed of board passers and non-board passers. The researchers used purposive sampling technique. The result utilized by using T-test Independent Sample to determine the comparison of General Weighted Average and Comprehensive Examination Result of Board Passers and Non Board Passers. At the end, it concluded that the General Weighted Average of Board Passers and Non-Board Passers shows that there is no significant difference, but the average showed a minimal variation. The Comprehensive Examination Result of Board Passers and Non-Board Passers result revealed that there is a significant difference. The performance of comprehensive examination that will test the overall knowledge of an individual and will determine whose more proficient will likely to have a higher score. The result of the comprehensive examination had an impact in the passing performance of board examination. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=board%20passers" title="board passers">board passers</a>, <a href="https://publications.waset.org/abstracts/search?q=comprehensive%20examination%20result" title=" comprehensive examination result"> comprehensive examination result</a>, <a href="https://publications.waset.org/abstracts/search?q=grade%20weighted%20average" title=" grade weighted average"> grade weighted average</a>, <a href="https://publications.waset.org/abstracts/search?q=non%20board%20passers" title=" non board passers"> non board passers</a> </p> <a href="https://publications.waset.org/abstracts/101314/a-comparative-analysis-of-grade-weighted-average-and-comprehensive-examination-result-of-non-board-passers-and-board-passers" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/101314.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">8573</span> The Effect of Oil Price Uncertainty on Food Price in South Africa</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Goodness%20C.%20Aye">Goodness C. Aye</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This paper examines the effect of the volatility of oil prices on food price in South Africa using monthly data covering the period 2002:01 to 2014:09. Food price is measured by the South African consumer price index for food while oil price is proxied by the Brent crude oil. The study employs the GARCH-in-mean VAR model, which allows the investigation of the effect of a negative and positive shock in oil price volatility on food price. The model also allows the oil price uncertainty to be measured as the conditional standard deviation of a one-step-ahead forecast error of the change in oil price. The results show that oil price uncertainty has a positive and significant effect on food price in South Africa. The responses of food price to a positive and negative oil price shocks is asymmetric. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=oil%20price%20volatility" title="oil price volatility">oil price volatility</a>, <a href="https://publications.waset.org/abstracts/search?q=food%20price" title=" food price"> food price</a>, <a href="https://publications.waset.org/abstracts/search?q=bivariate" title=" bivariate"> bivariate</a>, <a href="https://publications.waset.org/abstracts/search?q=GARCH-in-mean%20VAR" title=" GARCH-in-mean VAR"> GARCH-in-mean VAR</a>, <a href="https://publications.waset.org/abstracts/search?q=asymmetric" title=" asymmetric"> asymmetric</a> </p> <a href="https://publications.waset.org/abstracts/28399/the-effect-of-oil-price-uncertainty-on-food-price-in-south-africa" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/28399.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">479</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">8572</span> Optimal Design for SARMA(P,Q)L Process of EWMA Control Chart</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Yupaporn%20Areepong">Yupaporn Areepong</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The main goal of this paper is to study Statistical Process Control (SPC) with Exponentially Weighted Moving Average (EWMA) control chart when observations are serially-correlated. The characteristic of control chart is Average Run Length (ARL) which is the average number of samples taken before an action signal is given. Ideally, an acceptable ARL of in-control process should be enough large, so-called (ARL0). Otherwise it should be small when the process is out-of-control, so-called Average of Delay Time (ARL1) or a mean of true alarm. We find explicit formulas of ARL for EWMA control chart for Seasonal Autoregressive and Moving Average processes (SARMA) with Exponential white noise. The results of ARL obtained from explicit formula and Integral equation are in good agreement. In particular, this formulas for evaluating (ARL0) and (ARL1) be able to get a set of optimal parameters which depend on smoothing parameter (λ) and width of control limit (H) for designing EWMA chart with minimum of (ARL1). <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=average%20run%20length" title="average run length">average run length</a>, <a href="https://publications.waset.org/abstracts/search?q=optimal%20parameters" title=" optimal parameters"> optimal parameters</a>, <a href="https://publications.waset.org/abstracts/search?q=exponentially%20weighted%20moving%20average%20%28EWMA%29" title=" exponentially weighted moving average (EWMA)"> exponentially weighted moving average (EWMA)</a>, <a href="https://publications.waset.org/abstracts/search?q=control%20chart" title=" control chart"> control chart</a> </p> <a href="https://publications.waset.org/abstracts/10653/optimal-design-for-sarmapql-process-of-ewma-control-chart" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/10653.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">560</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">8571</span> Notes on Frames in Weighted Hardy Spaces and Generalized Weighted Composition Operators</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Shams%20Alyusof">Shams Alyusof</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This work is to enrich the studies of the frames due to their prominent role in pure mathematics as well as in applied mathematics and many applications in computer science and engineering. Recently, there are remarkable studies of operators that preserve frames on some spaces, and this research could be considered as an extension of such studies. Indeed, this paper is to we characterize weighted composition operators that preserve frames in weighted Hardy spaces on the open unit disk. Moreover, it shows that this characterization does not apply to generalized weighted composition operators on such spaces. Nevertheless, this study could be extended to provide more specific characterizations. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=frames" title="frames">frames</a>, <a href="https://publications.waset.org/abstracts/search?q=generalized%20weighted%20composition%20operators" title=" generalized weighted composition operators"> generalized weighted composition operators</a>, <a href="https://publications.waset.org/abstracts/search?q=weighted%20Hardy%20spaces" title=" weighted Hardy spaces"> weighted Hardy spaces</a>, <a href="https://publications.waset.org/abstracts/search?q=analytic%20functions" title=" analytic functions"> analytic functions</a> </p> <a href="https://publications.waset.org/abstracts/156372/notes-on-frames-in-weighted-hardy-spaces-and-generalized-weighted-composition-operators" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/156372.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">122</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">8570</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">97</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">8569</span> Distribution-Free Exponentially Weighted Moving Average Control Charts for Monitoring Process Variability </h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Chen-Fang%20Tsai">Chen-Fang Tsai</a>, <a href="https://publications.waset.org/abstracts/search?q=Shin-Li%20Lu"> Shin-Li Lu</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Distribution-free control chart is an oncoming area from the statistical process control charts in recent years. Some researchers have developed various nonparametric control charts and investigated the detection capability of these charts. The major advantage of nonparametric control charts is that the underlying process is not specifically considered the assumption of normality or any parametric distribution. In this paper, two nonparametric exponentially weighted moving average (EWMA) control charts based on nonparametric tests, namely NE-S and NE-M control charts, are proposed for monitoring process variability. Generally, weighted moving average (GWMA) control charts are extended by utilizing design and adjustment parameters for monitoring the changes in the process variability, namely NG-S and NG-M control charts. Statistical performance is also investigated on NG-S and NG-M control charts with run rules. Moreover, sensitivity analysis is performed to show the effects of design parameters under the nonparametric NG-S and NG-M control charts. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=Distribution-free%20control%20chart" title="Distribution-free control chart">Distribution-free control chart</a>, <a href="https://publications.waset.org/abstracts/search?q=EWMA%20control%20charts" title=" EWMA control charts"> EWMA control charts</a>, <a href="https://publications.waset.org/abstracts/search?q=GWMA%20control%20charts" title=" GWMA control charts"> GWMA control charts</a> </p> <a href="https://publications.waset.org/abstracts/88638/distribution-free-exponentially-weighted-moving-average-control-charts-for-monitoring-process-variability" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/88638.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">275</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">8568</span> Some Results for F-Minimal Hypersurfaces in Manifolds with Density</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=M.%20Abdelmalek">M. Abdelmalek</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this work, we study the hypersurfaces of constant weighted mean curvature embedded in weighted manifolds. We give a condition about these hypersurfaces to be minimal. This condition is given by the ellipticity of the weighted Newton transformations. We especially prove that two compact hypersurfaces of constant weighted mean curvature embedded in space forms and with the intersection in at least a point of the boundary must be transverse. The method is based on the calculus of the matrix of the second fundamental form in a boundary point and then the matrix associated with the Newton transformations. By equality, we find the weighted elementary symmetric function on the boundary of the hypersurface. We give in the end some examples and applications. Especially in Euclidean space, we use the above result to prove the Alexandrov spherical caps conjecture for the weighted case. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=weighted%20mean%20curvature" title="weighted mean curvature">weighted mean curvature</a>, <a href="https://publications.waset.org/abstracts/search?q=weighted%20manifolds" title=" weighted manifolds"> weighted manifolds</a>, <a href="https://publications.waset.org/abstracts/search?q=ellipticity" title=" ellipticity"> ellipticity</a>, <a href="https://publications.waset.org/abstracts/search?q=Newton%20transformations" title=" Newton transformations"> Newton transformations</a> </p> <a href="https://publications.waset.org/abstracts/160174/some-results-for-f-minimal-hypersurfaces-in-manifolds-with-density" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/160174.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">93</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">8567</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">143</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">8566</span> The Moment of the Optimal Average Length of the Multivariate Exponentially Weighted Moving Average Control Chart for Equally Correlated Variables</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Edokpa%20Idemudia%20Waziri">Edokpa Idemudia Waziri</a>, <a href="https://publications.waset.org/abstracts/search?q=Salisu%20S.%20Umar"> Salisu S. Umar</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The Hotellng’s T^2 is a well-known statistic for detecting a shift in the mean vector of a multivariate normal distribution. Control charts based on T have been widely used in statistical process control for monitoring a multivariate process. Although it is a powerful tool, the T statistic is deficient when the shift to be detected in the mean vector of a multivariate process is small and consistent. The Multivariate Exponentially Weighted Moving Average (MEWMA) control chart is one of the control statistics used to overcome the drawback of the Hotellng’s T statistic. In this paper, the probability distribution of the Average Run Length (ARL) of the MEWMA control chart when the quality characteristics exhibit substantial cross correlation and when the process is in-control and out-of-control was derived using the Markov Chain algorithm. The derivation of the probability functions and the moments of the run length distribution were also obtained and they were consistent with some existing results for the in-control and out-of-control situation. By simulation process, the procedure identified a class of ARL for the MEWMA control when the process is in-control and out-of-control. From our study, it was observed that the MEWMA scheme is quite adequate for detecting a small shift and a good way to improve the quality of goods and services in a multivariate situation. It was also observed that as the in-control average run length ARL0¬ or the number of variables (p) increases, the optimum value of the ARL0pt increases asymptotically and as the magnitude of the shift σ increases, the optimal ARLopt decreases. Finally, we use the example from the literature to illustrate our method and demonstrate its efficiency. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=average%20run%20length" title="average run length">average run length</a>, <a href="https://publications.waset.org/abstracts/search?q=markov%20chain" title=" markov chain"> markov chain</a>, <a href="https://publications.waset.org/abstracts/search?q=multivariate%20exponentially%20weighted%20moving%20average" title=" multivariate exponentially weighted moving average"> multivariate exponentially weighted moving average</a>, <a href="https://publications.waset.org/abstracts/search?q=optimal%20smoothing%20parameter" title=" optimal smoothing parameter"> optimal smoothing parameter</a> </p> <a href="https://publications.waset.org/abstracts/42648/the-moment-of-the-optimal-average-length-of-the-multivariate-exponentially-weighted-moving-average-control-chart-for-equally-correlated-variables" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/42648.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">422</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">8565</span> An EWMA P-Chart Based on Improved Square Root Transformation</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Saowanit%20Sukparungsee">Saowanit Sukparungsee</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Generally, the traditional Shewhart p chart has been developed by for charting the binomial data. This chart has been developed using the normal approximation with condition as low defect level and the small to moderate sample size. In real applications, however, are away from these assumptions due to skewness in the exact distribution. In this paper, a modified Exponentially Weighted Moving Average (EWMA) control chat for detecting a change in binomial data by improving square root transformations, namely ISRT p EWMA control chart. The numerical results show that ISRT p EWMA chart is superior to ISRT p chart for small to moderate shifts, otherwise, the latter is better for large shifts. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=number%20of%20defects" title="number of defects">number of defects</a>, <a href="https://publications.waset.org/abstracts/search?q=exponentially%20weighted%20moving%20average" title=" exponentially weighted moving average"> exponentially weighted moving average</a>, <a href="https://publications.waset.org/abstracts/search?q=average%20run%20length" title=" average run length"> average run length</a>, <a href="https://publications.waset.org/abstracts/search?q=square%20root%20transformations" title=" square root transformations"> square root transformations</a> </p> <a href="https://publications.waset.org/abstracts/10613/an-ewma-p-chart-based-on-improved-square-root-transformation" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/10613.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">440</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">8564</span> Price Effect Estimation of Tobacco on Low-wage Male Smokers: A Causal Mediation Analysis</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Kawsar%20Ahmed">Kawsar Ahmed</a>, <a href="https://publications.waset.org/abstracts/search?q=Hong%20Wang"> Hong Wang</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The study's goal was to estimate the causal mediation impact of tobacco tax before and after price hikes among low-income male smokers, with a particular emphasis on the effect estimating pathways framework for continuous and dichotomous variables. From July to December 2021, a cross-sectional investigation of observational data (n=739) was collected from Bangladeshi low-wage smokers. The Quasi-Bayesian technique, binomial probit model, and sensitivity analysis using a simulation of the computational tools R mediation package had been used to estimate the effect. After a price rise for tobacco products, the average number of cigarettes or bidis sticks taken decreased from 6.7 to 4.56. Tobacco product rising prices have a direct effect on low-income people's decisions to quit or lessen their daily smoking habits of Average Causal Mediation Effect (ACME) [effect=2.31, 95 % confidence interval (C.I.) = (4.71-0.00), p<0.01], Average Direct Effect (ADE) [effect=8.6, 95 percent (C.I.) = (6.8-0.11), p<0.001], and overall significant effects (p<0.001). Tobacco smoking choice is described by the mediated proportion of income effect, which is 26.1% less of following price rise. The curve of ACME and ADE is based on observational figures of the coefficients of determination that asses the model of hypothesis as the substantial consequence after price rises in the sensitivity analysis. To reduce smoking product behaviors, price increases through taxation have a positive causal mediation with income that affects the decision to limit tobacco use and promote low-income men's healthcare policy. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=causal%20mediation%20analysis" title="causal mediation analysis">causal mediation analysis</a>, <a href="https://publications.waset.org/abstracts/search?q=directed%20acyclic%20graphs" title=" directed acyclic graphs"> directed acyclic graphs</a>, <a href="https://publications.waset.org/abstracts/search?q=tobacco%20price%20policy" title=" tobacco price policy"> tobacco price policy</a>, <a href="https://publications.waset.org/abstracts/search?q=sensitivity%20analysis" title=" sensitivity analysis"> sensitivity analysis</a>, <a href="https://publications.waset.org/abstracts/search?q=pathway%20estimation" title=" pathway estimation"> pathway estimation</a> </p> <a href="https://publications.waset.org/abstracts/152123/price-effect-estimation-of-tobacco-on-low-wage-male-smokers-a-causal-mediation-analysis" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/152123.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">114</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">8563</span> A Theory and Empirical Analysis on the Efficency of Chinese Electricity Pricing</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Jianlin%20Wang">Jianlin Wang</a>, <a href="https://publications.waset.org/abstracts/search?q=Jiajia%20Zhao"> Jiajia Zhao</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This paper applies the theory and empirical method to examine the relationship between electricity price and coal price, as well as electricity and industry output, for China during Jan 1999-Dec 2012. Our results indicate that there is no any causality between coal price and electricity price under other factors are controlled. However, we found a bi-directional causality between electricity consumption and industry output. Overall, the electricity price set by China’s NDRC is inefficient, which lead to the electricity supply shortage after 2004. It is time to reform electricity price system for China’s reformers. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=electricity%20price" title="electricity price">electricity price</a>, <a href="https://publications.waset.org/abstracts/search?q=coal%20price" title=" coal price"> coal price</a>, <a href="https://publications.waset.org/abstracts/search?q=power%20supply" title=" power supply"> power supply</a>, <a href="https://publications.waset.org/abstracts/search?q=China" title=" China"> China</a> </p> <a href="https://publications.waset.org/abstracts/9560/a-theory-and-empirical-analysis-on-the-efficency-of-chinese-electricity-pricing" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/9560.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">472</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">8562</span> Co-Integration Model for Predicting Inflation Movement in Nigeria</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Salako%20Rotimi">Salako Rotimi</a>, <a href="https://publications.waset.org/abstracts/search?q=Oshungade%20Stephen"> Oshungade Stephen</a>, <a href="https://publications.waset.org/abstracts/search?q=Ojewoye%20Opeyemi"> Ojewoye Opeyemi</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The maintenance of price stability is one of the macroeconomic challenges facing Nigeria as a nation. This paper attempts to build a co-integration multivariate time series model for inflation movement in Nigeria using data extracted from the abstract of statistics of the Central Bank of Nigeria (CBN) from 2008 to 2017. The Johansen cointegration test suggests at least one co-integration vector describing the long run relationship between Consumer Price Index (CPI), Food Price Index (FPI) and Non-Food Price Index (NFPI). All three series show increasing pattern, which indicates a sign of non-stationary in each of the series. Furthermore, model predictability was established with root-mean-square-error, mean absolute error, mean average percentage error, and Theil’s unbiased statistics for n-step forecasting. The result depicts that the long run coefficient of a consumer price index (CPI) has a positive long-run relationship with the food price index (FPI) and non-food price index (NFPI). <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=economic" title="economic">economic</a>, <a href="https://publications.waset.org/abstracts/search?q=inflation" title=" inflation"> inflation</a>, <a href="https://publications.waset.org/abstracts/search?q=model" title=" model"> model</a>, <a href="https://publications.waset.org/abstracts/search?q=series" title=" series"> series</a> </p> <a href="https://publications.waset.org/abstracts/109868/co-integration-model-for-predicting-inflation-movement-in-nigeria" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/109868.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">245</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">8561</span> Forecast of the Small Wind Turbines Sales with Replacement Purchases and with or without Account of Price Changes </h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=V.%20Churkin">V. Churkin</a>, <a href="https://publications.waset.org/abstracts/search?q=M.%20Lopatin"> M. Lopatin</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The purpose of the paper is to estimate the US small wind turbines market potential and forecast the small wind turbines sales in the US. The forecasting method is based on the application of the Bass model and the generalized Bass model of innovations diffusion under replacement purchases. In the work an exponential distribution is used for modeling of replacement purchases. Only one parameter of such distribution is determined by average lifetime of small wind turbines. The identification of the model parameters is based on nonlinear regression analysis on the basis of the annual sales statistics which has been published by the American Wind Energy Association (AWEA) since 2001 up to 2012. The estimation of the US average market potential of small wind turbines (for adoption purchases) without account of price changes is 57080 (confidence interval from 49294 to 64866 at P = 0.95) under average lifetime of wind turbines 15 years, and 62402 (confidence interval from 54154 to 70648 at P = 0.95) under average lifetime of wind turbines 20 years. In the first case the explained variance is 90,7%, while in the second - 91,8%. The effect of the wind turbines price changes on their sales was estimated using generalized Bass model. This required a price forecast. To do this, the polynomial regression function, which is based on the Berkeley Lab statistics, was used. The estimation of the US average market potential of small wind turbines (for adoption purchases) in that case is 42542 (confidence interval from 32863 to 52221 at P = 0.95) under average lifetime of wind turbines 15 years, and 47426 (confidence interval from 36092 to 58760 at P = 0.95) under average lifetime of wind turbines 20 years. In the first case the explained variance is 95,3%, while in the second –95,3%. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=bass%20model" title="bass model">bass model</a>, <a href="https://publications.waset.org/abstracts/search?q=generalized%20bass%20model" title=" generalized bass model"> generalized bass model</a>, <a href="https://publications.waset.org/abstracts/search?q=replacement%20purchases" title=" replacement purchases"> replacement purchases</a>, <a href="https://publications.waset.org/abstracts/search?q=sales%20forecasting%20of%20innovations" title=" sales forecasting of innovations"> sales forecasting of innovations</a>, <a href="https://publications.waset.org/abstracts/search?q=statistics%20of%20sales%20of%20small%20wind%20turbines%20in%20the%20United%20States" title=" statistics of sales of small wind turbines in the United States"> statistics of sales of small wind turbines in the United States</a> </p> <a href="https://publications.waset.org/abstracts/25237/forecast-of-the-small-wind-turbines-sales-with-replacement-purchases-and-with-or-without-account-of-price-changes" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/25237.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">348</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">8560</span> Application of the Quantile Regression Approach to the Heterogeneity of the Fine Wine Prices</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Charles-Olivier%20Am%C3%A9d%C3%A9e-Manesme">Charles-Olivier Amédée-Manesme</a>, <a href="https://publications.waset.org/abstracts/search?q=Benoit%20Faye"> Benoit Faye</a>, <a href="https://publications.waset.org/abstracts/search?q=Eric%20Le%20Fur"> Eric Le Fur</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this paper, the heterogeneity of the Bordeaux Legends 50 wine market price segment is addressed. For this purpose, quantile regression is applied – with market segmentation based on wine bottle price quantile – and the hedonic price of wine attributes is computed for various price segments of the market. The approach is applied to a major privately held data set which consists of approximately 30,000 transactions over the 2003–2014 period. The findings suggest that the relative hedonic prices of several wine attributes differ significantly among deciles. In particular, the elasticity coefficient of the expert ratings shows strong variation among prices. If - as suggested in the literature - expert ratings have a positive influence on wine price on average, they have a clearly decreasing impact over the quantiles. Finally, the lower the wine price, the higher the potential for price appreciation over time. Other variables such as chateaux or vintage are also shown to vary across the distribution of wine prices. While enhancing our understanding of the complex market dynamics that underlie Bordeaux wines’ price, this research provides empirical evidence that the QR approach adequately captures heterogeneity among wine price ranges, which simultaneously applies to wine stock, vintage and auctions’ house. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=hedonics" title="hedonics">hedonics</a>, <a href="https://publications.waset.org/abstracts/search?q=market%20segmentation" title=" market segmentation"> market segmentation</a>, <a href="https://publications.waset.org/abstracts/search?q=quantile%20regression" title=" quantile regression"> quantile regression</a>, <a href="https://publications.waset.org/abstracts/search?q=heterogeneity" title=" heterogeneity"> heterogeneity</a>, <a href="https://publications.waset.org/abstracts/search?q=wine%20economics" title=" wine economics"> wine economics</a> </p> <a href="https://publications.waset.org/abstracts/70068/application-of-the-quantile-regression-approach-to-the-heterogeneity-of-the-fine-wine-prices" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/70068.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">342</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">8559</span> Intended-Actual First Asking/Offer Price Discrepancies and Their Impact on Negotiation Behaviour and Outcomes</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Liuyao%20Chai">Liuyao Chai</a>, <a href="https://publications.waset.org/abstracts/search?q=Colin%20Clark"> Colin Clark</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Analysis of 574 participants in a simulated two-person distributive negotiation revealed that the first price 245 (42.7%) of these participants actually asked/offered for the item under negotiation (a used car) differed from the first price they previously stated they intended to ask/offer during their negotiation. This discrepancy between a negotiator’s intended first asking/offer price and his/her actual first asking/offer price had a significant and economically consequential impact on both the course and the outcomes of the negotiations studied. Participants whose actual first price remained the same as their intended first price tended to secure better negotiation outcomes. Moreover, participants who changed their intended first price tended to obtain relatively lower outcomes regardless of whether their modified first announced price had created a negotiating position that was ‘stronger’ or ‘weaker’ than if they had opened with their intended first price. Subsequent investigation of over twenty negotiation behaviours and pre-negotiation perceptual variables within this dataset indicated that the three types of first price announcers—i.e. intended first asking/offer price ‘weakeners’, ‘maintainers’ and ‘strengtheners’— comprised persons who tended to have significantly different pre-negotiation perceptions and behaved in systematically different ways during their negotiation. Typically, the most negative, outcome-compromising consequences of changing, weakening or strengthening an intended first price occurred at the very beginning of a negotiation when participants exchanged their actual first asking/offer prices. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=business%20communication" title="business communication">business communication</a>, <a href="https://publications.waset.org/abstracts/search?q=negotiation" title=" negotiation"> negotiation</a>, <a href="https://publications.waset.org/abstracts/search?q=persuasion" title=" persuasion"> persuasion</a>, <a href="https://publications.waset.org/abstracts/search?q=intended%20first%20asking%2Foffer%20prices" title=" intended first asking/offer prices"> intended first asking/offer prices</a>, <a href="https://publications.waset.org/abstracts/search?q=bargaining" title=" bargaining"> bargaining</a> </p> <a href="https://publications.waset.org/abstracts/24182/intended-actual-first-askingoffer-price-discrepancies-and-their-impact-on-negotiation-behaviour-and-outcomes" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/24182.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">373</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">8558</span> Designing Price Stability Model of Red Cayenne Pepper Price in Wonogiri District, Centre Java, Using ARCH/GARCH Method</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Fauzia%20Dianawati">Fauzia Dianawati</a>, <a href="https://publications.waset.org/abstracts/search?q=Riska%20W.%20Purnomo"> Riska W. Purnomo</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Food and agricultural sector become the biggest sector contributing to inflation in Indonesia. Especially in Wonogiri district, red cayenne pepper was the biggest sector contributing to inflation on 2016. A national statistic proved that in recent five years red cayenne pepper has the highest average level of fluctuation among all commodities. Some factors, like supply chain, price disparity, production quantity, crop failure, and oil price become the possible factor causes high volatility level in red cayenne pepper price. Therefore, this research tries to find the key factor causing fluctuation on red cayenne pepper by using ARCH/GARCH method. The method could accommodate the presence of heteroscedasticity in time series data. At the end of the research, it is statistically found that the second level of supply chain becomes the biggest part contributing to inflation with 3,35 of coefficient in fluctuation forecasting model of red cayenne pepper price. This model could become a reference to the government to determine the appropriate policy in maintaining the price stability of red cayenne pepper. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=ARCH%2FGARCH" title="ARCH/GARCH">ARCH/GARCH</a>, <a href="https://publications.waset.org/abstracts/search?q=forecasting" title=" forecasting"> forecasting</a>, <a href="https://publications.waset.org/abstracts/search?q=red%20cayenne%20pepper" title=" red cayenne pepper"> red cayenne pepper</a>, <a href="https://publications.waset.org/abstracts/search?q=volatility" title=" volatility"> volatility</a>, <a href="https://publications.waset.org/abstracts/search?q=supply%20chain" title=" supply chain"> supply chain</a> </p> <a href="https://publications.waset.org/abstracts/79137/designing-price-stability-model-of-red-cayenne-pepper-price-in-wonogiri-district-centre-java-using-archgarch-method" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/79137.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">186</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">8557</span> Study of NGL Feed Price Calculation for a Typical NGL Fractionation Plant</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Simin%20Eydivand">Simin Eydivand</a>, <a href="https://publications.waset.org/abstracts/search?q=Ali%20Ghanadieslami"> Ali Ghanadieslami</a>, <a href="https://publications.waset.org/abstracts/search?q=Reza%20Amiri"> Reza Amiri</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Natural gas liquids (NGLs) are light hydrocarbons that are dissolved in associated or non‐associated natural gas in a hydrocarbon reservoir and are produced within a gas stream. There are different ways to calculate the price of NGL. In this study, a spreadsheet calculation method is used for calculation of NGL price with an attractive economy of IRR 25%. For a typical NGL Plant with 3,200,000 t/y capacity of investment and operation of 90% capacity to have IRR 25%, the price of NGL is calculated 277 $/t. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=natural%20gas%20liquid" title="natural gas liquid">natural gas liquid</a>, <a href="https://publications.waset.org/abstracts/search?q=NGL" title=" NGL"> NGL</a>, <a href="https://publications.waset.org/abstracts/search?q=LPG" title=" LPG"> LPG</a>, <a href="https://publications.waset.org/abstracts/search?q=price" title=" price"> price</a>, <a href="https://publications.waset.org/abstracts/search?q=NGL%20fractionation" title=" NGL fractionation"> NGL fractionation</a>, <a href="https://publications.waset.org/abstracts/search?q=NF" title=" NF"> NF</a>, <a href="https://publications.waset.org/abstracts/search?q=investment" title=" investment"> investment</a>, <a href="https://publications.waset.org/abstracts/search?q=IRR" title=" IRR"> IRR</a>, <a href="https://publications.waset.org/abstracts/search?q=NPV" title=" NPV"> NPV</a> </p> <a href="https://publications.waset.org/abstracts/33705/study-of-ngl-feed-price-calculation-for-a-typical-ngl-fractionation-plant" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/33705.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">408</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">8556</span> Multi-Criteria Decision Approach to Performance Measurement Techniques Data Envelopment Analysis: Case Study of Kerman City’s Parks</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Ali%20A.%20Abdollahi">Ali A. Abdollahi</a> </p> <p class="card-text"><strong>Abstract:</strong></p> During the last several decades, scientists have consistently applied Multiple Criteria Decision-Making methods in making decisions about multi-faceted, complicated subjects. While making such decisions and in order to achieve more accurate evaluations, they have regularly used a variety of criteria instead of applying just one Optimum Evaluation Criterion. The method presented here utilizes both ‘quantity’ and ‘quality’ to assess the function of the Multiple-Criteria method. Applying Data envelopment analysis (DEA), weighted aggregated sum product assessment (WASPAS), Weighted Sum Approach (WSA), Analytic Network Process (ANP), and Charnes, Cooper, Rhodes (CCR) methods, we have analyzed thirteen parks in Kerman city. It further indicates that the functions of WASPAS and WSA are compatible with each other, but also that their deviation from DEA is extensive. Finally, the results for the CCR technique do not match the results of the DEA technique. Our study indicates that the ANP method, with the average rate of 1/51, ranks closest to the DEA method, which has an average rate of 1/49. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=multiple%20criteria%20decision%20making" title="multiple criteria decision making">multiple criteria decision making</a>, <a href="https://publications.waset.org/abstracts/search?q=Data%20envelopment%20analysis%20%28DEA%29" title=" Data envelopment analysis (DEA)"> Data envelopment analysis (DEA)</a>, <a href="https://publications.waset.org/abstracts/search?q=Charnes%20Cooper%20Rhodes%20%28CCR%29" title=" Charnes Cooper Rhodes (CCR)"> Charnes Cooper Rhodes (CCR)</a>, <a href="https://publications.waset.org/abstracts/search?q=Weighted%20Sum%20Approach%20%28WSA%29" title=" Weighted Sum Approach (WSA)"> Weighted Sum Approach (WSA)</a> </p> <a href="https://publications.waset.org/abstracts/92557/multi-criteria-decision-approach-to-performance-measurement-techniques-data-envelopment-analysis-case-study-of-kerman-citys-parks" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/92557.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">221</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">8555</span> General Framework for Price Regulation of Container Terminals</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Murat%20Yildiz">Murat Yildiz</a>, <a href="https://publications.waset.org/abstracts/search?q=Burcu%20Yildiz"> Burcu Yildiz</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Price Cap Regulation is a form of economic regulation designed in the 1980s in the United Kingdom. Price cap regulation sets a cap on the price that the utility provider can charge. The cap is set according to several economic factors, such as the price cap index, expected efficiency savings and inflation. It has been used by several countries as a regulatory regime in several sectors. Container port privatization is still in early stages in some countries. Lack of a general framework can be an impediment to privatization. This paper aims a general framework to comprising decisions to be made for variables which are able to accommodate the variety of container terminals. Several approaches that may be needed as well as a passage between approaches. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=Price%20Cap%20Regulation" title="Price Cap Regulation">Price Cap Regulation</a>, <a href="https://publications.waset.org/abstracts/search?q=ports%20privatization" title=" ports privatization"> ports privatization</a>, <a href="https://publications.waset.org/abstracts/search?q=container%20terminal%20price%20regime" title=" container terminal price regime"> container terminal price regime</a>, <a href="https://publications.waset.org/abstracts/search?q=earning%20sharing" title=" earning sharing"> earning sharing</a> </p> <a href="https://publications.waset.org/abstracts/46297/general-framework-for-price-regulation-of-container-terminals" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/46297.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">362</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">8554</span> Breast Cancer Survivability Prediction via Classifier Ensemble</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Mohamed%20Al-Badrashiny">Mohamed Al-Badrashiny</a>, <a href="https://publications.waset.org/abstracts/search?q=Abdelghani%20Bellaachia"> Abdelghani Bellaachia</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This paper presents a classifier ensemble approach for predicting the survivability of the breast cancer patients using the latest database version of the Surveillance, Epidemiology, and End Results (SEER) Program of the National Cancer Institute. The system consists of two main components; features selection and classifier ensemble components. The features selection component divides the features in SEER database into four groups. After that it tries to find the most important features among the four groups that maximizes the weighted average F-score of a certain classification algorithm. The ensemble component uses three different classifiers, each of which models different set of features from SEER through the features selection module. On top of them, another classifier is used to give the final decision based on the output decisions and confidence scores from each of the underlying classifiers. Different classification algorithms have been examined; the best setup found is by using the decision tree, Bayesian network, and Na¨ıve Bayes algorithms for the underlying classifiers and Na¨ıve Bayes for the classifier ensemble step. The system outperforms all published systems to date when evaluated against the exact same data of SEER (period of 1973-2002). It gives 87.39% weighted average F-score compared to 85.82% and 81.34% of the other published systems. By increasing the data size to cover the whole database (period of 1973-2014), the overall weighted average F-score jumps to 92.4% on the held out unseen test set. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=classifier%20ensemble" title="classifier ensemble">classifier ensemble</a>, <a href="https://publications.waset.org/abstracts/search?q=breast%20cancer%20survivability" title=" breast cancer survivability"> breast cancer survivability</a>, <a href="https://publications.waset.org/abstracts/search?q=data%20mining" title=" data mining"> data mining</a>, <a href="https://publications.waset.org/abstracts/search?q=SEER" title=" SEER"> SEER</a> </p> <a href="https://publications.waset.org/abstracts/42621/breast-cancer-survivability-prediction-via-classifier-ensemble" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/42621.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">329</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">8553</span> An Inquiry of the Impact of Flood Risk on Housing Market with Enhanced Geographically Weighted Regression</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Lin-Han%20Chiang%20Hsieh">Lin-Han Chiang Hsieh</a>, <a href="https://publications.waset.org/abstracts/search?q=Hsiao-Yi%20Lin"> Hsiao-Yi Lin</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This study aims to determine the impact of the disclosure of flood potential map on housing prices. The disclosure is supposed to mitigate the market failure by reducing information asymmetry. On the other hand, opponents argue that the official disclosure of simulated results will only create unnecessary disturbances on the housing market. This study identifies the impact of the disclosure of the flood potential map by comparing the hedonic price of flood potential before and after the disclosure. The flood potential map used in this study is published by Taipei municipal government in 2015, which is a result of a comprehensive simulation based on geographical, hydrological, and meteorological factors. The residential property sales data of 2013 to 2016 is used in this study, which is collected from the actual sales price registration system by the Department of Land Administration (DLA). The result shows that the impact of flood potential on residential real estate market is statistically significant both before and after the disclosure. But the trend is clearer after the disclosure, suggesting that the disclosure does have an impact on the market. Also, the result shows that the impact of flood potential differs by the severity and frequency of precipitation. The negative impact for a relatively mild, high frequency flood potential is stronger than that for a heavy, low possibility flood potential. The result indicates that home buyers are of more concern to the frequency, than the intensity of flood. Another contribution of this study is in the methodological perspective. The classic hedonic price analysis with OLS regression suffers from two spatial problems: the endogeneity problem caused by omitted spatial-related variables, and the heterogeneity concern to the presumption that regression coefficients are spatially constant. These two problems are seldom considered in a single model. This study tries to deal with the endogeneity and heterogeneity problem together by combining the spatial fixed-effect model and geographically weighted regression (GWR). A series of literature indicates that the hedonic price of certain environmental assets varies spatially by applying GWR. Since the endogeneity problem is usually not considered in typical GWR models, it is arguable that the omitted spatial-related variables might bias the result of GWR models. By combing the spatial fixed-effect model and GWR, this study concludes that the effect of flood potential map is highly sensitive by location, even after controlling for the spatial autocorrelation at the same time. The main policy application of this result is that it is improper to determine the potential benefit of flood prevention policy by simply multiplying the hedonic price of flood risk by the number of houses. The effect of flood prevention might vary dramatically by location. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=flood%20potential" title="flood potential">flood potential</a>, <a href="https://publications.waset.org/abstracts/search?q=hedonic%20price%20analysis" title=" hedonic price analysis"> hedonic price analysis</a>, <a href="https://publications.waset.org/abstracts/search?q=endogeneity" title=" endogeneity"> endogeneity</a>, <a href="https://publications.waset.org/abstracts/search?q=heterogeneity" title=" heterogeneity"> heterogeneity</a>, <a href="https://publications.waset.org/abstracts/search?q=geographically-weighted%20regression" title=" geographically-weighted regression"> geographically-weighted regression</a> </p> <a href="https://publications.waset.org/abstracts/70025/an-inquiry-of-the-impact-of-flood-risk-on-housing-market-with-enhanced-geographically-weighted-regression" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/70025.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">290</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">8552</span> The Influence of Oil Price Fluctuations on Macroeconomics Variables of the Kingdom of Saudi Arabia</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Khalid%20Mujaljal">Khalid Mujaljal</a>, <a href="https://publications.waset.org/abstracts/search?q=Hassan%20Alhajhoj"> Hassan Alhajhoj</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This paper empirically investigates the influence of oil price fluctuations on the key macroeconomic variables of the Kingdom of Saudi Arabia using unrestricted VAR methodology. Two analytical tools- Granger-causality and variance decomposition are used. The Granger-causality test reveals that almost all specifications of oil price shocks significantly Granger-cause GDP and demonstrates evidence of causality between oil price changes and money supply (M3) and consumer price index percent (CPIPC) in the case of positive oil price shocks. Surprisingly, almost all specifications of oil price shocks do not Granger-cause government expenditure. The outcomes from variance decomposition analysis suggest that positive oil shocks contribute about 25 percent in causing inflation in the country. Also, contribution of symmetric linear oil price shocks and asymmetric positive oil price shocks is significant and persistent with 25 percent explaining variation in world consumer price index till end of the period. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=Granger%20causality" title="Granger causality">Granger causality</a>, <a href="https://publications.waset.org/abstracts/search?q=oil%20prices%20changes" title=" oil prices changes"> oil prices changes</a>, <a href="https://publications.waset.org/abstracts/search?q=Saudi%20Arabian%20economy" title=" Saudi Arabian economy"> Saudi Arabian economy</a>, <a href="https://publications.waset.org/abstracts/search?q=variance%20decomposition" title=" variance decomposition"> variance decomposition</a> </p> <a href="https://publications.waset.org/abstracts/7014/the-influence-of-oil-price-fluctuations-on-macroeconomics-variables-of-the-kingdom-of-saudi-arabia" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/7014.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">324</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">8551</span> Risk Factors’ Analysis on Shanghai Carbon Trading </h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Zhaojun%20Wang">Zhaojun Wang</a>, <a href="https://publications.waset.org/abstracts/search?q=Zongdi%20Sun"> Zongdi Sun</a>, <a href="https://publications.waset.org/abstracts/search?q=Zhiyuan%20Liu"> Zhiyuan Liu</a> </p> <p class="card-text"><strong>Abstract:</strong></p> First of all, the carbon trading price and trading volume in Shanghai are transformed by Fourier transform, and the frequency response diagram is obtained. Then, the frequency response diagram is analyzed and the Blackman filter is designed. The Blackman filter is used to filter, and the carbon trading time domain and frequency response diagram are obtained. After wavelet analysis, the carbon trading data were processed; respectively, we got the average value for each 5 days, 10 days, 20 days, 30 days, and 60 days. Finally, the data are used as input of the Back Propagation Neural Network model for prediction. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=Shanghai%20carbon%20trading" title="Shanghai carbon trading">Shanghai carbon trading</a>, <a href="https://publications.waset.org/abstracts/search?q=carbon%20trading%20price" title=" carbon trading price"> carbon trading price</a>, <a href="https://publications.waset.org/abstracts/search?q=carbon%20trading%20volume" title=" carbon trading volume"> carbon trading volume</a>, <a href="https://publications.waset.org/abstracts/search?q=wavelet%20analysis" title=" wavelet analysis"> wavelet analysis</a>, <a href="https://publications.waset.org/abstracts/search?q=BP%20neural%20network%20model" title=" BP neural network model"> BP neural network model</a> </p> <a href="https://publications.waset.org/abstracts/81327/risk-factors-analysis-on-shanghai-carbon-trading" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/81327.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">391</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">8550</span> Post-Contrast Susceptibility Weighted Imaging vs. Post-Contrast T1 Weighted Imaging for Evaluation of Brain Lesions</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Sujith%20Rajashekar%20Swamy">Sujith Rajashekar Swamy</a>, <a href="https://publications.waset.org/abstracts/search?q=Meghana%20Rajashekara%20Swamy"> Meghana Rajashekara Swamy</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Although T1-weighted gadolinium-enhanced imaging (T1-Gd) has its established clinical role in diagnosing brain lesions of infectious and metastatic origins, the use of post-contrast susceptibility-weighted imaging (SWI) has been understudied. This observational study aims to explore and compare the prominence of brain parenchymal lesions between T1-Gd and SWI-Gd images. A cross-sectional study design was utilized to analyze 58 patients with brain parenchymal lesions using T1-Gd and SWI-Gd scanning techniques. Our results indicated that SWI-Gd enhanced the conspicuity of metastatic as well as infectious brain lesions when compared to T1-Gd. Consequently, it can be used as an adjunct to T1-Gd for post-contrast imaging, thereby avoiding additional contrast administration. Improved conspicuity of brain lesions translates directly to enhanced patient outcomes, and hence SWI-Gd imaging proves useful to meet that endpoint. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=susceptibility%20weighted" title="susceptibility weighted">susceptibility weighted</a>, <a href="https://publications.waset.org/abstracts/search?q=T1%20weighted" title=" T1 weighted"> T1 weighted</a>, <a href="https://publications.waset.org/abstracts/search?q=brain%20lesions" title=" brain lesions"> brain lesions</a>, <a href="https://publications.waset.org/abstracts/search?q=gadolinium%20contrast" title=" gadolinium contrast"> gadolinium contrast</a> </p> <a href="https://publications.waset.org/abstracts/160957/post-contrast-susceptibility-weighted-imaging-vs-post-contrast-t1-weighted-imaging-for-evaluation-of-brain-lesions" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/160957.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">129</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">8549</span> Tobacco Taxation and the Heterogeneity of Smokers' Responses to Price Increases</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Simone%20Tedeschi">Simone Tedeschi</a>, <a href="https://publications.waset.org/abstracts/search?q=Francesco%20Crespi"> Francesco Crespi</a>, <a href="https://publications.waset.org/abstracts/search?q=Paolo%20Liberati"> Paolo Liberati</a>, <a href="https://publications.waset.org/abstracts/search?q=Massimo%20Paradiso"> Massimo Paradiso</a>, <a href="https://publications.waset.org/abstracts/search?q=Antonio%20Sciala"> Antonio Sciala</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This paper aims at contributing to the understanding of smokers’ responses to cigarette prices increases with a focus on heterogeneity, both across individuals and price levels. To do this, a stated preference quasi-experimental design grounded in a random utility framework is proposed to evaluate the effect on smokers’ utility of the price level and variation, along with social conditioning and health impact perception. The analysis is based on individual-level data drawn from a unique survey gathering very detailed information on Italian smokers’ habits. In particular, qualitative information on the individual reactions triggered by changes in prices of different magnitude and composition are exploited. The main findings stemming from the analysis are the following; the average price elasticity of cigarette consumption is comparable with previous estimates for advanced economies (-.32). However, the decomposition of this result across five latent-classes of smokers, reveals extreme heterogeneity in terms of price responsiveness, implying a potential price elasticity that ranges between 0.05 to almost 1. Such heterogeneity is in part explained by observable characteristics such as age, income, gender, education as well as (current and lagged) smoking intensity. Moreover, price responsiveness is far from being independent from the size of the prospected price increase. Finally, by comparing even and uneven price variations, it is shown that uniform across-brand price increases are able to limit the scope of product substitutions and downgrade. Estimated price-response heterogeneity has significant implications for tax policy. Among them, first, it provides evidence and a rationale for why the aggregate price elasticity is likely to follow a strictly increasing pattern as a function of the experienced price variation. This information is crucial for forecasting the effect of a given tax-driven price change on tax revenue. Second, it provides some guidance on how to design excise tax reforms to balance public health and revenue goals. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=smoking%20behaviour" title="smoking behaviour">smoking behaviour</a>, <a href="https://publications.waset.org/abstracts/search?q=preference%20heterogeneity" title=" preference heterogeneity"> preference heterogeneity</a>, <a href="https://publications.waset.org/abstracts/search?q=price%20responsiveness" title=" price responsiveness"> price responsiveness</a>, <a href="https://publications.waset.org/abstracts/search?q=cigarette%20taxation" title=" cigarette taxation"> cigarette taxation</a>, <a href="https://publications.waset.org/abstracts/search?q=random%20utility%20models" title=" random utility models"> random utility models</a> </p> <a href="https://publications.waset.org/abstracts/84680/tobacco-taxation-and-the-heterogeneity-of-smokers-responses-to-price-increases" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/84680.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">164</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=volume%20weighted%20average%20price&page=2">2</a></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=volume%20weighted%20average%20price&page=3">3</a></li> <li class="page-item"><a class="page-link" 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