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selection</title> <meta name="description" content="Search results for: stock selection"> <meta name="keywords" content="stock selection"> <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 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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="stock selection"> <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> 3155</div> </div> </div> </div> <h1 class="mt-3 mb-3 text-center" style="font-size:1.6rem;">Search results for: stock selection</h1> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">3155</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">419</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">3154</span> Investment Decision among Public Sector Retirees: A Behavioural Finance View </h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Bisi%20S.%20Olawoyin">Bisi S. Olawoyin </a> </p> <p class="card-text"><strong>Abstract:</strong></p> This study attempts an exploration into behavioural finance in which the traditional assumptions of expected utility maximization with rational investors in efficient markets are dropped. It reviews prior research and evidence about how psychological biases affect investors behaviour and stock selection. This study examined the relationship between demographic variables and financial behaviour biases among public sector retirees who invested in the Nigerian Stock Exchange prior to their retirement. By using questionnaire survey method, a total of 214 valid convenient samples were collected in order to determine how specific demographic and psychological trait affect stock selection between dividend paying and non-dividend paying stocks. Descriptive statistics and OLS were used to analyse the results. Findings showed that most of the retirees prefer dividend paying stocks in few years preceding their retirement but still hold on to their non-dividend paying stock on retirement. A significant difference also exists between senior and junior retirees in preference for non-dividend paying stocks. These findings are consistent with the clientele theories of dividend. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=behavioural%20finance" title="behavioural finance">behavioural finance</a>, <a href="https://publications.waset.org/abstracts/search?q=clientele%20theories" title=" clientele theories"> clientele theories</a>, <a href="https://publications.waset.org/abstracts/search?q=dividend%20paying%20stocks" title=" dividend paying stocks"> dividend paying stocks</a>, <a href="https://publications.waset.org/abstracts/search?q=stock%20selection" title=" stock selection"> stock selection</a> </p> <a href="https://publications.waset.org/abstracts/84208/investment-decision-among-public-sector-retirees-a-behavioural-finance-view" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/84208.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">3153</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">3152</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">3151</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">3150</span> Markowitz and Implementation of a Multi-Objective Evolutionary Technique Applied to the Colombia Stock Exchange (2009-2015)</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Feijoo%20E.%20Colomine%20Duran">Feijoo E. Colomine Duran</a>, <a href="https://publications.waset.org/abstracts/search?q=Carlos%20E.%20Pe%C3%B1aloza%20Corredor"> Carlos E. Peñaloza Corredor</a> </p> <p class="card-text"><strong>Abstract:</strong></p> There modeling component selection financial investment (Portfolio) a variety of problems that can be addressed with optimization techniques under evolutionary schemes. For his feature, the problem of selection of investment components of a dichotomous relationship between two elements that are opposed: The Portfolio Performance and Risk presented by choosing it. This relationship was modeled by Markowitz through a media problem (Performance) - variance (risk), ie must Maximize Performance and Minimize Risk. This research included the study and implementation of multi-objective evolutionary techniques to solve these problems, taking as experimental framework financial market equities Colombia Stock Exchange between 2009-2015. Comparisons three multiobjective evolutionary algorithms, namely the Nondominated Sorting Genetic Algorithm II (NSGA-II), the Strength Pareto Evolutionary Algorithm 2 (SPEA2) and Indicator-Based Selection in Multiobjective Search (IBEA) were performed using two measures well known performance: The Hypervolume indicator and R_2 indicator, also it became a nonparametric statistical analysis and the Wilcoxon rank-sum test. The comparative analysis also includes an evaluation of the financial efficiency of the investment portfolio chosen by the implementation of various algorithms through the Sharpe ratio. It is shown that the portfolio provided by the implementation of the algorithms mentioned above is very well located between the different stock indices provided by the Colombia Stock Exchange. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=finance" title="finance">finance</a>, <a href="https://publications.waset.org/abstracts/search?q=optimization" title=" optimization"> optimization</a>, <a href="https://publications.waset.org/abstracts/search?q=portfolio" title=" portfolio"> portfolio</a>, <a href="https://publications.waset.org/abstracts/search?q=Markowitz" title=" Markowitz"> Markowitz</a>, <a href="https://publications.waset.org/abstracts/search?q=evolutionary%20algorithms" title=" evolutionary algorithms"> evolutionary algorithms</a> </p> <a href="https://publications.waset.org/abstracts/56680/markowitz-and-implementation-of-a-multi-objective-evolutionary-technique-applied-to-the-colombia-stock-exchange-2009-2015" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/56680.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">302</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">3149</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">3148</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">3147</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">3146</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">3145</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">3144</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">3143</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">3142</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">3141</span> Transport Mode Selection under Lead Time Variability and Emissions Constraint</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Chiranjit%20Das">Chiranjit Das</a>, <a href="https://publications.waset.org/abstracts/search?q=Sanjay%20Jharkharia"> Sanjay Jharkharia</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This study is focused on transport mode selection under lead time variability and emissions constraint. In order to reduce the carbon emissions generation due to transportation, organization has often faced a dilemmatic choice of transport mode selection since logistic cost and emissions reduction are complementary with each other. Another important aspect of transportation decision is lead-time variability which is least considered in transport mode selection problem. Thus, in this study, we provide a comprehensive mathematical based analytical model to decide transport mode selection under emissions constraint. We also extend our work through analysing the effect of lead time variability in the transport mode selection by a sensitivity analysis. In order to account lead time variability into the model, two identically normally distributed random variables are incorporated in this study including unit lead time variability and lead time demand variability. Therefore, in this study, we are addressing following questions: How the decisions of transport mode selection will be affected by lead time variability? How lead time variability will impact on total supply chain cost under carbon emissions? To accomplish these objectives, a total transportation cost function is developed including unit purchasing cost, unit transportation cost, emissions cost, holding cost during lead time, and penalty cost for stock out due to lead time variability. A set of modes is available to transport each node, in this paper, we consider only four transport modes such as air, road, rail, and water. Transportation cost, distance, emissions level for each transport mode is considered as deterministic and static in this paper. Each mode is having different emissions level depending on the distance and product characteristics. Emissions cost is indirectly affected by the lead time variability if there is any switching of transport mode from lower emissions prone transport mode to higher emissions prone transport mode in order to reduce penalty cost. We provide a numerical analysis in order to study the effectiveness of the mathematical model. We found that chances of stock out during lead time will be higher due to the higher variability of lead time and lad time demand. Numerical results show that penalty cost of air transport mode is negative that means chances of stock out zero, but, having higher holding and emissions cost. Therefore, air transport mode is only selected when there is any emergency order to reduce penalty cost, otherwise, rail and road transport is the most preferred mode of transportation. Thus, this paper is contributing to the literature by a novel approach to decide transport mode under emissions cost and lead time variability. This model can be extended by studying the effect of lead time variability under some other strategic transportation issues such as modal split option, full truck load strategy, and demand consolidation strategy etc. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=carbon%20emissions" title="carbon emissions">carbon emissions</a>, <a href="https://publications.waset.org/abstracts/search?q=inventory%20theoretic%20model" title=" inventory theoretic model"> inventory theoretic model</a>, <a href="https://publications.waset.org/abstracts/search?q=lead%20time%20variability" title=" lead time variability"> lead time variability</a>, <a href="https://publications.waset.org/abstracts/search?q=transport%20mode%20selection" title=" transport mode selection"> transport mode selection</a> </p> <a href="https://publications.waset.org/abstracts/68507/transport-mode-selection-under-lead-time-variability-and-emissions-constraint" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/68507.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">434</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">3140</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">3139</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">3138</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> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">3137</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">3136</span> The Influence of the Company's Financial Performance and Macroeconomic Factors to Stock Return</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Angrita%20Denziana">Angrita Denziana</a>, <a href="https://publications.waset.org/abstracts/search?q=Haninun"> Haninun</a>, <a href="https://publications.waset.org/abstracts/search?q=Hepiana%20Patmarina"> Hepiana Patmarina</a>, <a href="https://publications.waset.org/abstracts/search?q=Ferdinan%20Fatah"> Ferdinan Fatah</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The aims of the study are to determine the effect of the company's financial performance with Return on Asset (ROA) and Return on Equity (ROE) indicators. The macroeconomic factors with the indicators of Indonesia interest rate (SBI) and exchange rate on stock returns of non-financial companies listed in IDX. The results of this study indicate that the variable of ROA has negative effect on stock returns, ROE has a positive effect on stock returns, and the variable interest rate and exchange rate of SBI has positive effect on stock returns. From the analysis data by using regression model, independent variables ROA, ROE, SBI interest rate and the exchange rate very significant (p value < 0.01). Thus, all the above variable can be used as the basis for investment decision making for investment in Indonesia Stock Exchange (IDX) mainly for shares in the non- financial companies. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=ROA" title="ROA">ROA</a>, <a href="https://publications.waset.org/abstracts/search?q=ROE" title=" ROE"> ROE</a>, <a href="https://publications.waset.org/abstracts/search?q=interest%20rate" title=" interest rate"> interest rate</a>, <a href="https://publications.waset.org/abstracts/search?q=exchange%20rate" title=" exchange rate"> exchange rate</a>, <a href="https://publications.waset.org/abstracts/search?q=stock%20return" title=" stock return "> stock return </a> </p> <a href="https://publications.waset.org/abstracts/21185/the-influence-of-the-companys-financial-performance-and-macroeconomic-factors-to-stock-return" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/21185.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">429</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">3135</span> Stock Price Informativeness and Profit Warnings: Empirical Analysis </h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Adel%20Almasarwah">Adel Almasarwah</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This study investigates the nature of association between profit warnings and stock price informativeness in the context of Jordan as an emerging country. The analysis is based on the response of stock price synchronicity to profit warnings percentages that have been published in Jordanian firms throughout the period spanning 2005–2016 in the Amman Stock Exchange. The standard of profit warnings indicators have related negatively to stock price synchronicity in Jordanian firms, meaning that firms with a high portion of profit warnings integrate with more firm-specific information into stock price. Robust regression was used rather than OLS as a parametric test to overcome the variances inflation factor (VIF) and heteroscedasticity issues recognised as having occurred during running the OLS regression; this enabled us to obtained stronger results that fall in line with our prediction that higher profit warning encourages firm investors to collect and process more firm-specific information than common market information. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=Profit%20Warnings" title="Profit Warnings">Profit Warnings</a>, <a href="https://publications.waset.org/abstracts/search?q=Jordanian%20Firms" title=" Jordanian Firms"> Jordanian Firms</a>, <a href="https://publications.waset.org/abstracts/search?q=Stock%20Price%20Informativeness" title=" Stock Price Informativeness"> Stock Price Informativeness</a>, <a href="https://publications.waset.org/abstracts/search?q=Synchronicity" title=" Synchronicity"> Synchronicity</a> </p> <a href="https://publications.waset.org/abstracts/120633/stock-price-informativeness-and-profit-warnings-empirical-analysis" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/120633.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">142</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">3134</span> The Impact of Bitcoin on Stock Market Performance</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Oliver%20Takawira">Oliver Takawira</a>, <a href="https://publications.waset.org/abstracts/search?q=Thembi%20Hope"> Thembi Hope</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This study will analyse the relationship between Bitcoin price movements and the Johannesburg stock exchange (JSE). The aim is to determine whether Bitcoin price movements affect the stock market performance. As crypto currencies continue to gain prominence as a safe asset during periods of economic distress, this raises the question of whether Bitcoin’s prosperity could affect investment in the stock market. To identify the existence of a short run and long run linear relationship, the study will apply the Autoregressive Distributed Lag Model (ARDL) bounds test and a Vector Error Correction Model (VECM) after testing the data for unit roots and cointegration using the Augmented Dicker Fuller (ADF) and Phillips-Perron (PP). The Non-Linear Auto Regressive Distributed Lag (NARDL) will then be used to check if there is a non-linear relationship between bitcoin prices and stock market prices. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=bitcoin" title="bitcoin">bitcoin</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=interest%20rates" title=" interest rates"> interest rates</a>, <a href="https://publications.waset.org/abstracts/search?q=ARDL" title=" ARDL"> ARDL</a> </p> <a href="https://publications.waset.org/abstracts/150006/the-impact-of-bitcoin-on-stock-market-performance" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/150006.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">106</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">3133</span> The Effect of Behavioral and Risk Factors of Investment Growth on Stock Returns</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Majid%20Lotfi%20Ghahroud">Majid Lotfi Ghahroud</a>, <a href="https://publications.waset.org/abstracts/search?q=Seyed%20Jalal%20Tabatabaei"> Seyed Jalal Tabatabaei</a>, <a href="https://publications.waset.org/abstracts/search?q=Ebrahim%20Karami"> Ebrahim Karami</a>, <a href="https://publications.waset.org/abstracts/search?q=AmirArsalan%20Ghergherechi"> AmirArsalan Ghergherechi</a>, <a href="https://publications.waset.org/abstracts/search?q=Amir%20Ali%20Saeidi"> Amir Ali Saeidi</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this study, the relationship between investment growth and stock returns of companies listed in Tehran Stock Exchange and whether their relationship -behavioral or risk factors- are discussed. Generally, there are two perspectives; risk-based approach and behavioral approach. According to the risk-based approach due to increase investment, systemic risk and consequently the stock returns are reduced. But due to the second approach, an excessive optimism or pessimism leads to assuming stock price with high investment growth in the past, higher than its intrinsic value and the price of stocks with lower investment growth, less than its intrinsic value. The investigation period is eight years from 2007 to 2014. The sample consisted of all companies listed on the Tehran Stock Exchange. The method is a portfolio test, and the analysis is based on the t-student test (t-test). The results indicate that there is a negative relationship between investment growth and stock returns of companies and this negative correlation is stronger for firms with higher cash flow. Also, the negative relationship between asset growth and stock returns is due to behavioral factors. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=behavioral%20theory" title="behavioral theory">behavioral theory</a>, <a href="https://publications.waset.org/abstracts/search?q=investment%20growth" title=" investment growth"> investment growth</a>, <a href="https://publications.waset.org/abstracts/search?q=risk-based%20theory" title=" risk-based theory"> risk-based theory</a>, <a href="https://publications.waset.org/abstracts/search?q=stock%20returns" title=" stock returns"> stock returns</a> </p> <a href="https://publications.waset.org/abstracts/95312/the-effect-of-behavioral-and-risk-factors-of-investment-growth-on-stock-returns" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/95312.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">156</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">3132</span> Corporate Governance and Share Prices: Firm Level Review in Turkey</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Raif%20Parlakkaya">Raif Parlakkaya</a>, <a href="https://publications.waset.org/abstracts/search?q=Ahmet%20Diken"> Ahmet Diken</a>, <a href="https://publications.waset.org/abstracts/search?q=Erkan%20Kara"> Erkan Kara</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This paper examines the relationship between corporate governance rating and stock prices of 26 Turkish firms listed in Turkish stock exchange (Borsa Istanbul) by using panel data analysis over five-year period. The paper also investigates the stock performance of firms with governance rating with regards to the market portfolio (i.e. BIST 100 Index) both prior and after governance scoring began. The empirical results show that there is no relation between corporate governance rating and stock prices when using panel data for annual variation in both rating score and stock prices. Further analysis indicates surprising results that while the selected firms outperform the market significantly prior to rating, the same performance does not continue afterwards. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=corporate%20governance" title="corporate governance">corporate governance</a>, <a href="https://publications.waset.org/abstracts/search?q=stock%20price" title=" stock price"> stock price</a>, <a href="https://publications.waset.org/abstracts/search?q=performance" title=" performance"> performance</a>, <a href="https://publications.waset.org/abstracts/search?q=panel%20data%20analysis" title=" panel data analysis "> panel data analysis </a> </p> <a href="https://publications.waset.org/abstracts/29587/corporate-governance-and-share-prices-firm-level-review-in-turkey" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/29587.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">393</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">3131</span> Testing the Weak Form Efficiency of Islamic Stock Market: Empirical Evidence from Indonesia</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Herjuno%20Bagus%20Wicaksono">Herjuno Bagus Wicaksono</a>, <a href="https://publications.waset.org/abstracts/search?q=Emma%20Almira%20Fauni"> Emma Almira Fauni</a>, <a href="https://publications.waset.org/abstracts/search?q=Salma%20Amelia%20Dina"> Salma Amelia Dina</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The Efficient Market Hypothesis (EMH) states that, in an efficient capital market, price fully reflects the information available in the market. This theory has influenced many investors behavior in trading in the stock market. Advanced researches have been conducted to test the efficiency of the stock market in particular countries. Indonesia, as one of the emerging countries, has performed substantial growth in the past years. Hence, this paper aims to examine the efficiency of Islamic stock market in Indonesia in its weak form. The daily stock price data from Indonesia Sharia Stock Index (ISSI) for the period October 2015 to October 2016 were used to do the statistical tests: Run Test and Serial Correlation Test. The results show that there is no serial correlation between the current price with the past prices and the market follows the random walk. This research concludes that Indonesia Islamic stock market is weak form efficient. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=efficient%20market%20hypothesis" title="efficient market hypothesis">efficient market hypothesis</a>, <a href="https://publications.waset.org/abstracts/search?q=Indonesia%20sharia%20stock%20index" title=" Indonesia sharia stock index"> Indonesia sharia stock index</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=weak%20form%20efficiency" title=" weak form efficiency"> weak form efficiency</a> </p> <a href="https://publications.waset.org/abstracts/61095/testing-the-weak-form-efficiency-of-islamic-stock-market-empirical-evidence-from-indonesia" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/61095.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">460</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">3130</span> A Mathematical Equation to Calculate Stock Price of Different Growth Model</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Weiping%20Liu">Weiping Liu</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This paper presents an equation to calculate stock prices of different growth model. This equation is mathematically derived by using discounted cash flow method. It has the advantages of being very easy to use and very accurate. It can still be used even when the first stage is lengthy. This equation is more generalized because it can be used for all the three popular stock price models. It can be programmed into financial calculator or electronic spreadsheets. In addition, it can be extended to a multistage model. It is more versatile and efficient than the traditional methods. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=stock%20price" title="stock price">stock price</a>, <a href="https://publications.waset.org/abstracts/search?q=multistage%20model" title=" multistage model"> multistage model</a>, <a href="https://publications.waset.org/abstracts/search?q=different%20growth%20model" title=" different growth model"> different growth model</a>, <a href="https://publications.waset.org/abstracts/search?q=discounted%20cash%20flow%20method" title=" discounted cash flow method"> discounted cash flow method</a> </p> <a href="https://publications.waset.org/abstracts/12664/a-mathematical-equation-to-calculate-stock-price-of-different-growth-model" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/12664.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">406</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">3129</span> On the Influence of the Covid-19 Pandemic on Tunisian Stock Market: By Sector Analysis</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Nadia%20Sghaier">Nadia Sghaier</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this paper, we examine the influence of the COVID-19 pandemic on the performance of the Tunisian stock market and 12 sectors over a recent period from 23 March 2020 to 18 August 2021, including several waves and the introduction of vaccination. The empirical study is conducted using cointegration techniques which allows for long and short-run relationships. The obtained results indicate that both daily growth in confirmed cases and deaths have a negative and significant effect on the stock market returns. In particular, this effect differs across sectors. It seems more pronounced in financial, consumer goods and industrials sectors. These findings have important implications for investors to predict the behavior of the stock market or sectors returns and to implement hedging strategies during the COVID-19 pandemic. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=Tunisian%20stock%20market" title="Tunisian stock market">Tunisian stock market</a>, <a href="https://publications.waset.org/abstracts/search?q=sectors" title=" sectors"> sectors</a>, <a href="https://publications.waset.org/abstracts/search?q=COVID-19%20pandemic" title=" COVID-19 pandemic"> COVID-19 pandemic</a>, <a href="https://publications.waset.org/abstracts/search?q=cointegration%20techniques" title=" cointegration techniques"> cointegration techniques</a> </p> <a href="https://publications.waset.org/abstracts/141180/on-the-influence-of-the-covid-19-pandemic-on-tunisian-stock-market-by-sector-analysis" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/141180.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">201</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">3128</span> Long-Run Relationship among Tehran Stock Exchange and the GCC Countries Financial Markets, Before and After 2007/2008 Financial Crisis</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Mohammad%20Hossein%20Ranjbar">Mohammad Hossein Ranjbar</a>, <a href="https://publications.waset.org/abstracts/search?q=Mahdi%20Bagheri"> Mahdi Bagheri</a>, <a href="https://publications.waset.org/abstracts/search?q=B.%20Shivaraj"> B. Shivaraj</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This study attempts to investigate the relationship between stock market of Iran and GCC countries stock exchanges. Eight markets were included: the stock market of Iran, Kuwait, Bahrain, Qatar, Saudi Arabia, Dubai, Abu Dhabi and Oman. Daily country market indices were collected from January 2005 to December 2010. The potential time-varying behaviors of long-run stock market relationship among selected markets are tested applying correlation test, Augmented Dick Fuller test (ADF), Bilateral and Multilateral Cointegration (Johansen), and the Granger Causality test. The findings suggest that stock market of Iran is negatively correlated with most of the selected markets in the whole duration. But contemporaneous correlations among the eight selected markets are increased positively in period of financial crises. Bilateral Cointegration between selected markets suggests that there is no integration between Tehran stock exchange and other selected markets. Among other markets, except the stock market of Dubai and Abu Dhabi as a one pair, are not cointegrated in whole, but in duration of financial crises integration between selected markets are increased. Finally, investigation of the casual relationship among eight financial markets suggests there are unidirectional and bidirectional causal relationship among some of stock market indices. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=financial%20crises" title="financial crises">financial crises</a>, <a href="https://publications.waset.org/abstracts/search?q=Middle%20East" title=" Middle East"> Middle East</a>, <a href="https://publications.waset.org/abstracts/search?q=stock%20market%20integration" title=" stock market integration"> stock market integration</a>, <a href="https://publications.waset.org/abstracts/search?q=Granger%20Causality%20test" title=" Granger Causality test"> Granger Causality test</a>, <a href="https://publications.waset.org/abstracts/search?q=ARDL%20test" title=" ARDL test"> ARDL test</a> </p> <a href="https://publications.waset.org/abstracts/36061/long-run-relationship-among-tehran-stock-exchange-and-the-gcc-countries-financial-markets-before-and-after-20072008-financial-crisis" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/36061.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">394</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">3127</span> Nexus of Pakistan Stock Exchange with World's Top Five Stock Markets after Launching China Pakistan Economic Corridor</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Abdul%20Rauf">Abdul Rauf</a>, <a href="https://publications.waset.org/abstracts/search?q=Xiaoxing%20Liu"> Xiaoxing Liu</a>, <a href="https://publications.waset.org/abstracts/search?q=Waqas%20Amin"> Waqas Amin</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Stock markets are fascinating more and more conductive to each other due to liberalization and globalization trends in recent years. China Pakistan Economic Corridor (CPEC) has dragged Pakistan stock exchange to the new heights and global investors are making investments to reap its benefits. So, in investors and government perspective, the study focuses co-integration of Pakistan stock exchange with world’s five big economies i-e US, China, England, Japan, and France. The time period of study is seven years i-e 2010 to 2016 and daily values of major indices of corresponding stock exchanges collected. All variables of that particular study are stationary at first difference confirmed by unit root test. The study Johansen system co integration test for analysis of data along with Granger causality test is performed for result purpose. Co integration test asserted that Pakistan stock exchange integrated with Shanghai stock exchange (SSE) and NIKKEI stock exchange in short run. Granger causality test also proclaimed these results. But NASDAQ, FTSE, DAX not co integrated and Granger cause at a short run but long run these markets are bonded with Pakistan stock exchange (KSE). VECM also confirmed this liaison in short and long run. Investors, therefore, need to be updated regarding co-integration of world’s stock exchanges to ensure well diversified and risk adjusted high returns. Equally, governments also need updated status so that they could reduce co-integration through multiple steps and hence drag investors for diversified investment. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=CPEC" title="CPEC">CPEC</a>, <a href="https://publications.waset.org/abstracts/search?q=DAX" title=" DAX"> DAX</a>, <a href="https://publications.waset.org/abstracts/search?q=FTSE" title=" FTSE"> FTSE</a>, <a href="https://publications.waset.org/abstracts/search?q=liberalization" title=" liberalization"> liberalization</a>, <a href="https://publications.waset.org/abstracts/search?q=NASDAQ" title=" NASDAQ"> NASDAQ</a>, <a href="https://publications.waset.org/abstracts/search?q=NIKKEI" title=" NIKKEI"> NIKKEI</a>, <a href="https://publications.waset.org/abstracts/search?q=SSE" title=" SSE"> SSE</a>, <a href="https://publications.waset.org/abstracts/search?q=stock%20markets" title=" stock markets"> stock markets</a> </p> <a href="https://publications.waset.org/abstracts/78053/nexus-of-pakistan-stock-exchange-with-worlds-top-five-stock-markets-after-launching-china-pakistan-economic-corridor" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/78053.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">302</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">3126</span> The Effect of COVID-19 Transmission, Lockdown Measures, and Vaccination on Stock Market Returns</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Belhouchet%20Selma">Belhouchet Selma</a>, <a href="https://publications.waset.org/abstracts/search?q=Ben%20Amar%20Anis"> Ben Amar Anis</a> </p> <p class="card-text"><strong>Abstract:</strong></p> We examine the impact of COVID-19 transmission, containment measures, and vaccination growth on daily stock market returns for the G7 countries (Canada, France, Germany, Italy, Japan, the United Kingdom, and the United States) from January 22, 2020, to August 31, 2021, more than a year and a half after COVID-19. For this objective, we use panel pooled ordinary least squares regressions. Our findings indicate that the spread of the pandemic has a negative impact on the daily performance of the world's seven main stock markets. Government measures to improve stock market returns are no longer successful. Furthermore, our findings demonstrate that immunization efforts in G7 nations do not increase stock market performance in these countries. A variety of robustness tests back up our conclusions. Our findings have far-reaching implications for investors, governments, and regulators not only in the G7 countries but also in all developed countries and all countries globally. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=COVID-19" title="COVID-19">COVID-19</a>, <a href="https://publications.waset.org/abstracts/search?q=G7%20stock%20market" title=" G7 stock market"> G7 stock market</a>, <a href="https://publications.waset.org/abstracts/search?q=containment%20measures" title=" containment measures"> containment measures</a>, <a href="https://publications.waset.org/abstracts/search?q=vaccination" title=" vaccination"> vaccination</a> </p> <a href="https://publications.waset.org/abstracts/155046/the-effect-of-covid-19-transmission-lockdown-measures-and-vaccination-on-stock-market-returns" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/155046.pdf" target="_blank" class="btn 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