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This study aims to analyze the effect of the exchange rate on stock returns (SR) mediated by fundamental factors, which are represented by return on assets (ROA), debt equity ratio (DER) and earnings per share (EPS), in listed telecommunications sub-sector industrial companies. on the Indonesian Stock Exchange for the 2015-2022 period. This thesis is also to see how financial signals can influence investor perceptions and their impact on SR. The data used is secondary data obtained from the Indonesia Stock Exchange for telecommunications sub-sector companies for the period 2015-2022 and Bank Indonesia data for the IDR-USD exchange rate. This study uses the exchange rate as the dependent variable, stock returns as the independent variable, and ROA, DER and EPS as mediating variables. The analysis technique using the Structural Equation Model (SEM) approach using Partial Least Square (PLS) software, namely Smart PLS software. The results of the study proved that ROA had a not significant positive effect on SR, DER had a significant positive effect on SR, EPS had a significant positive effect on SR, ER had an insignificant positive effect on ROA, ER had an insignificant negative effect on DER, ER had an insignificant negative effect on EPS and ER has a significant negative effect on SR. Furthermore, ER has no significant positive effect on SR mediated by ROA, ER has no significant negative effect on SR mediated by DER, ER has no significant negative effect on SR mediated by EPS. [ABSTRACT FROM AUTHOR]

This study aims to determine the influence of fundamental factors of companies and systematic risks on stock returns. The type of data used in this study is secondary data. The data is obtained from annual reports and financial reports sourced from www.idx.co.id. The population used in the study is manufacturing companies listed on the Indonesia Stock Exchange (IDX) for the period 2018 - 2021. The samples used in this study were 42 manufacturing companies listed on the IDX that met the criteria. Data were analyzed using multiple linear regression method. The results of this study indicate that the enterprise's fundamental factors affect stock returns. There are significant differences in the variable size of enterprise asset sizes before and during the Covid-19 pandemic. However, there were no significant differences in liquidity variables, debt to equity ratio, return on equity, earnings per share, price earnings ratio and systematic risk before and during the Covid-19 pandemic. [ABSTRACT FROM AUTHOR]

This study provides evidence in support of the size effect, which posits that smaller companies generate greater profits in both rapidly developing markets and volatile markets. Furthermore, the results of the current study indicate that the application of operating leverage does not exert any discernible influence on stock returns. The empirical evidence derived from data obtained from non-financial companies listed on the KSE-100 Index leads us to the conclusion that the Pakistani market exhibits adherence to the CAPM, Fama, and French Models. The aforementioned proof was unearthed subsequent to our thorough examination of the market. To provide greater precision, the metrics utilized for assessing the magnitude of a company encompass the debt-to-equity ratio (DOL) and the aggregate assets held by the entity. In order to achieve the objective of assessing the influence of firm size and operating leverage on stock returns, a fixed effect regression model is employed. This action is undertaken with the intention of achieving the intended result. The analysis yielded findings indicating a negative correlation between firm size and share returns. There is no observed association between the application of operating leverage and the resultant returns generated by firms in the Pakistani market. [ABSTRACT FROM AUTHOR]

In the past two years, the global and Indonesian economies have been severely impacted by the COVID-19 pandemic, leading to below-target and negative growth rates worldwide. Indonesia declared the pandemic in March 2020, resulting in disruptions and lower-than-expected economic growth, with the first quarter of 2020 recording 2.97% growth compared to a consensus of 3.5-4.0%. Key sectors like manufacturing, retail, construction, and mining contracted, while household consumption dropped to 2.84% from 5.01% the previous year. This summary presents inflation and economic growth data in Indonesia as of October 2020 from the Central Statistics Agency. The research outcomes serve as reference material for government policy-making during crises, offer insights to infrastructure issuers in the capital market, assist investors in stock transactions and projections, and provide general knowledge about Indonesia's capital market. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Research in Economics, Politics & Finance / Ekonomi, Politika & Finans Arastirmalari Dergisi is the property of Journal of Research in Economics, Politics & Finance and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Objective Financial markets are considered to be a kind of complex network due to the interaction and interrelationship of its various actors. Therefore, the development of stock communication networks is an important issue for discovering potential connections between different companies. Therefore, the purpose of this research is to investigate and analyze the communication structure of companies in the capital market based on price, return, and trading volume of stock with a network approach. Methods This study employs a quantitative research methodology, specifically focusing on network analysis. The data were collected in the period between 2017 and 2021 and analyzed using the network analysis method and with the help of Excel 2021, SPSS 26, UCINET 6, and its complementary package NetDraw. In addition to the general analysis and review of the price, returns, and trading volume of the stock correlation network, the performance of each node in the network was also investigated using micro-indices. Centrality is one of the most important micro-concepts of network analysis, which examines the influence and importance of people in the network. Also, it was studied with three indices of degree, betweenness, and closeness of centrality of network nodes. Results The results indicated that as the correlation basis expands, there is a decrease in communication between different companies along with an increase in irregularity. The higher the correlation basis, the less likely it is to be affected by a common variable or interaction, which will reduce the correlation between stocks. In addition, there are companies in the communicative network that are in a better position than the rest. They may have higher connections, faster access to information, and greater influence over other units' price changes. As a result, these companies can play a decisive and leading role, or in other words, the role of key and influential actors in the governing structure. Also, the results showed that in the second period of 2021 compared to the first period, communication networks were much more erratic and scattered. Conclusion Considering the importance of capital market communication networks and the decisive role of key companies, relationship pattern analysis helps to increase transparency, reduce risk, and, consequently, improve decision-making, policy-making, portfolio optimization, etc by revealing the network structure of the capital market. The results of this research can lead to a better understanding of the forces that create the communication structure of companies and enable policymakers to make better decisions. Therefore, all users are suggested to pay attention to the communication structure governing the companies in the capital market and the role and impact of their position on the advancement of the company's goals in their decisions and to consider this communication structure and the way power is distributed. [ABSTRACT FROM AUTHOR]

This paper analyses the impact of Ukraine–Russia conflict on stock markets in Europe. We consider the stock markets of nine EU countries and Russia. The analysis consists of day-firm which includes the time between 24 November 2021 and 23 May 2022. We consider ordinary least squared (OLS) and fixed effects as baseline models. Additionally, we consider the impact of this conflict on stock return for several months, the elasticity test, the instrumental variable—two-stage least squared (2SLS) approach for the robustness test and endogeneity concerns. We find evidence of the negative impact of the Ukraine–Russia conflict on stock return of that stock markets. In addition, our finding indicates that the impact of this war on the mining construction and manufacturing sectors is greater than on other sectors because Russia and Ukraine are the key suppliers or exporters of mining and manufacturing sector. Our finding also indicates that Ukraine–Russia conflict largely affects stock return of Russian stocks because Russia is directly involved in the conflict. [ABSTRACT FROM AUTHOR]

The purpose of this research is to study and analyze the composition of the risk management committee and audit committee, and to develop a performance evaluation form of the composition of the risk management committee and audit committee regarding prediction of the return of companies registered in the Stock Exchange of Thailand. Samples used in this study are 317 companies in 5 years interval between 2017 – 2021. Path analysis is used in this study. In addition, seven experts in the related fields are invited to an in-depth interview and the results are summarized in accordance with the questionnaire in order to support the results that are in line with the hypothesis. The results of statistical analysis will be used to develop the Performance Evaluation Form of the Composition of the Risk Management Committee and Audit Committee. [ABSTRACT FROM AUTHOR]

Fluctuations in returns from investment in stocks make these risky. This factor should be kept in mind in stock investment decisions, which determines the relevance of this research. Through the study, the volatility in the stock returns of BRICS nations is analysed for inferring on the riskiness associated with investing in the respective nations, which is the aim of the research. For this study, the daily returns of five indexes representing each of the nation namely Ibovespa (Brazil), Moex (Russia), Nifty 50 (India), Hang Seng Index (HSI, China), and FTSE/JSE All Share Index (JALSH, South Africa) for a period of 14 years are collected and analysed. Both unconditional and conditional volatility in returns is analysed for each of the nations for imparting clearer and more comprehensive picture of the volatility in returns. Such an in-depth and long period analysis of volatility of the returns of the emerging BRICS economies is a novelty of the research that determined that no volatility model can be said as perfect for all economies for all time. The GARCH (1, 1) model was used to study for the returns of all the five indexes. The results of the study point out that the daily returns of all these indexes are heteroscedastic, implying presence of varying variance. Accordingly, the study м that the BRICS nations’ index returns are more volatile and riskier, and authors are recommended to invest in those indexes with lesser conditional volatility.

The relationship between investor sentiment and market dynamics is a highly intriguing research topic for both academics and the financial industry. By using Spearman rank correlation analysis, this paper aims to explore investors’ decision-making behavior (rational and irrational) on stock returns during and after the COVID-19 outbreak. While irrational factors of the study were measured by the Google Search Volume Index and trading volume, rational factors were measured by profitability and size. The study used three different characteristics of subsectors manufacturing industry namely Food and Beverage, Pharmacy, and Cigarettes that are listed in the Indonesia Stock Market. To the best of our knowledge, our study is the first to examine and compare the level of rationality of investors in a wide range of industries and sectors during and after the COVID-19 pandemic. Our finding supports the notion that both sentiments have an effect on stock returns indicating that cognitions, emotions, and the noise of traders still have an impact on the market. While overall rational sentiment has a more significant correlation with stock returns during the economic recovery phase, there was a highly significant correlation between irrational factors and stock returns during pandemic uncertainty conditions. Moreover, investors tend to be irrational and overreact when making investment decisions in Cigarette sectors during the COVID-19 pandemic. In contrast, after the pandemic, the correlation of rational sentiment of investors toward the Pharmacy industry is still higher than others.

This study investigates the market response to the timeliness of audit reports, specifically before and during the coronavirus disease 2020 (COVID-19) pandemic. We use the earnings response coefficient (ERC) as our proxy to assess the market reaction to the timeliness of audit reports. We applied the purposive sampling method to all companies listed on the Indonesia Stock Exchange (IDX), except for the financial industry, and obtained 977 firm-year observations as our final sample. Using linear multiple regression models in our analysis, we discovered no indication of a market response to the timeliness of audit reports for our full sample during 2018–2020. However, we find evidence that during the COVID-19 pandemic in 2020, the market reacted more positively to the audit report timeliness compared to the pre-COVID-19-pandemic period. Our results indicate that investors were more tolerant of delayed audit reports during the COVID-19 pandemic due to the increased audit efforts and longer time needed to gather sufficient evidence to issue audit reports.

The nexus between stock return and macroeconomic indicators have been a debatable phenomenon for a long time. It has also be one of the major issues for domestic and foreign investors in building efficient and optimum stock portfolio in the capital market. However, the unstable macroeconomic indicators adversely affect the level of stock return in the Nigerian capital market. Against this background, this study investigates the effect of macroeconomic factors on stock return in the Nigerian capital market. The study employed secondary data obtained from Nigeria Stock Exchange (NSE) fact book and Central Bank of Nigeria (CBN) statistical bulletin within the period of 1998 to 2019. The data obtained was subjected to Autoregressive Distribution Lag (ARDL) method of analysis. Findings revealed that money supply and aggregate industrial production positively and significantly affect stock return with co-efficient and P-value at (β=0.466098, P

This study aims to investigate investor sentiment and its effect on the industrial sector in Indonesia. In the study, investor sentiment was extracted from data obtained from search engines. Then the data were used to see how the sentiment affected the stock return in each listed industrial company. Fifteen industrial sector companies listed on the stock exchange were selected; each was analyzed for their search volume and the effect on stock returns using panel data regression from March 2020 to April 2022. The result shows that investor sentiment affects the level of stock returns in the industrial sector in Indonesia. This result indicates that with the increase in search volume on search engines, which reflects positive sentiment, there will be an increase in stock trading transactions and vice versa. This study's findings will help investors make investment decisions, especially in the industrial sector.

Purpose — This study aims to investigate the influence of macroeconomic factors, including economic growth, inflation, the rupiah exchange rate, and interest rates, as well as corporate financial performance indicators such as leverage and profitability, on the stock returns of Indonesian Property and Real Estate Sub-Sector companies. Method — The research data consists of annual data obtained from the Indonesia Stock Exchange, the Indonesia Central Bureau of Statistics, and Bank Indonesia for the period from 2017 to 2021. The research population comprises 36 Property and Real Estate companies listed on the Indonesia Stock Exchange. Out of these, 28 companies meet the sample requirements. The analysis employs panel data regression to examine the data. Result — The results indicate that inflation and exchange rates have a negative and statistically significant impact on stock returns. On the other hand, economic growth, interest rates, return on equity, and the debt-to-equity ratio exhibit a positive influence on stock returns, although these effects are not statistically significant. Contribution — This study's distinctive contribution is its focused analysis of the Property and Real Estate Sub-Sector in Indonesia. It stands out by exploring the intricate relationship between macroeconomic factors and financial performance variables concerning the stock returns of companies within this sub-sector. This nuanced approach provides valuable insights into a specific industry within the Indonesian market, shedding light on previously unexplored dynamics and contributing to a deeper understanding of how these factors affect stock returns in this context.

The launch of China's STAR market (officially known as the Science and Technology Innovation Board of Shanghai Stock Exchange) caused a significant drop in stock prices in existing stock markets in the Shanghai and Shenzhen stock exchanges. This study examines whether innovative firms showed more resilience to the shock caused by the launch of the STAR market. Using a sample of Chinese A-share listed firms, we find that firms with higher innovation had significantly higher stock returns during the shock period. This suggests that the STAR market launch induced investors to pay more attention to firm innovation and prompted them to reward innovations to a greater extent. This finding remains intact after an array of robustness tests. Moreover, this effect was more pronounced in non-state-owned enterprises and firms with higher product market competition. Additional analyses suggest that investors prefer firms with higher quality of innovation. Overall, this study finds that innovation plays an important role in capital markets; that is, innovation helps firms resist shock from the issuance of new shares. [ABSTRACT FROM AUTHOR]

• The model shows how "money matters" in determining stock prices. • Money supply influences the demand for stocks and positively affects their prices. • Overpricing or underpricing of stocks depends on the money supply in the economy. • Monetary policy affects stock prices by changing money supply. • Monetary policy may cause a disconnect between the stock market and the real economy. This study develops a simple model that shows how money matters in the determination of stock prices. When investors have different opinions on the stock's value and face market frictions, the money supply in an economy influences the demand for stocks and hence positively affects stock prices. Unlike the discounted-cash-flow model, the present model indicates that stock prices routinely depart from the fundamentals; overpricing or underpricing occurs depending on the amount of money in the economy. The results of the model suggest that stock prices fluctuate because of money supply changes and that monetary policy may cause a disconnect between the stock market and the real economy. [ABSTRACT FROM AUTHOR]

Manufacturing companies in Indonesia support the government's role in the development of the economic growth in the country. However, the Covid-19 pandemic has caused problems in making a profit. Therefore, the main problem of this study is to find out and analyze how net profit margin and earning per share affect stock return. Second, knowing and analyzing capital structure as an intervening variable that relates the effect of net profit margin and earning per share to stock return. This study explores the theoretical model and empirical results of how net profit margin and earning per share affects stock return through capital structure. The sampling method was carried out using the purposive sampling method, a data source collection technique that determines the sample with certain considerations. There were 25 companies that were sampled in this study. The data processing was done by multiple linear regression analysis. From various empirical results, there is still little research on the ability of capital structure as a intervening variable to analyze manufacturing companies listed on the Indonesia Stock Exchange. This research is expected to contribute to further research and facilitate the government to approach the development of manufacturing companies to encourage the economy. Meanwhile, investors can be informed about the company's stock return. The importance of this research can be useful for companies in providing solutions on how to increase net profit margin and earning per share by increasing stock return through capital structure factors. [ABSTRACT FROM AUTHOR]

The purpose of the extant study was to examine the effects of monetary and financial shocks on stock return in Iran's economy for the 1983-2016 period using the Autoregression method. This was applied research in terms of objective and a descriptive study in terms of method. Liquidity and government expenditure was selected as monetary and financial shocks, and research was conducted for the time interval of 1983-2016. Data analysis was done through the SVAR method and Eviews software. In this case, the return stock index was used as a representation of return stock. The results obtained from Granger causality indicated a strong relationship between government expenditure in production and the stock return index. Moreover, the sock of this variable had a negative effect on the stock exchange index, explaining 70% of the longrun variance in prediction error of this index. In addition to the Granger causality between liquidity and return stock exchange, the effect of this variable on the stock return index was positive and significant for 13 years. Accordingly, liquidity explained 51% of the prediction error variance of the efficiency index within the long term. There was also a Granger causality between inflation and return stock exchange, and the effect of its shock on the efficiency index was negative and significant for five periods explaining 46% of the long-run prediction error variance of the efficiency index. [ABSTRACT FROM AUTHOR]

Copyright of Itobiad: Journal of the Human & Social Science Researches / İnsan ve Toplum Bilimleri Araştırmaları Dergisi is the property of Itobiad: Journal of the Human & Social Science Researches and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

In recent years, a great deal of attention has been devoted to the use of neural networks in portfolio management, particularly in the prediction of stock prices. Building a more profitable portfolio with less risk has always been a challenging task. In this study, we propose a model to build a portfolio according to an equity-market-neutral (EMN) investment strategy. In this portfolio, the selection of stocks comprises two steps: a prediction of the individual returns of stocks using LSTM neural network, followed by a ranking of these stocks according to their predicted returns. The stocks with the best predicted returns and those with the worst predicted returns constitute, respectively, the long side and the short side of the portfolio to be built. The proposed model has two key benefits. First, data from historical quotes and technical and fundamental indicators are used in the LSTM network to provide good predictions. Second, the EMN strategy allows for the funding of long-position stocks by short-sell-position stocks, thus hedging the market risk. The results show that the built portfolios performed better compared to the benchmarks. Nonetheless, performance slowed down during the COVID-19 pandemic. [ABSTRACT FROM AUTHOR]

Copyright of Bingol University Journal of Economics & Administrative Science is the property of Bingol University Journal of Economics & Administrative Science and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The returns obtained from investment decisions made by businesses, individuals, and organizations. Utilizing panel data regression, the research collected data from the annual reports and financial statements of mining firms listed in the Indonesian sharia stock index between 2016 and 2020. The findings suggest that ROA, ROE, and PER positively impact stock returns. Effective management of these variables by companies, leading to higher profits, incentivises investor engagement. However, EPS does not significantly influence stock returns, as low earnings per share fail to accurately reflect the anticipated returns for investors, diminishing investor interest. Therefore, it can be concluded that ROA, ROE, EPS, and PER collectively influence stock returns. [ABSTRACT FROM AUTHOR]

The capital market has an important influence on improving the economy in Indonesia, every company who wants to increase the capital will invest in the Capital Market. The company's financial performance is the main thing that potential investors will see before deciding to invest. There are several ways to measure financial performance, one of which is by using performance on value through Economic Value Added (EVA) and Market Value Added (MVA). In addition to EVA and MVA, potential investors also pay attention to the company's stock price. The main purpose of potential investors investing is to get benefits in the form of stock returns. The purpose of this scientific article The Effect of EVA, MVA and Stock Price on Stock Return is to build a hypotheses for each variables that can be applied by future research in the Field of Financial Management Science. The writing method in the scientific article uses library research methods through Mendeley, Google Scholar, and other academic online application. The results of the scientific article are: 1) EVA affects Stock Return; 2) MVA affects Stock Return; and 3) Stock Price affects Stock Return. [ABSTRACT FROM AUTHOR]

Objective: Contratum strategies are hybrid strategies in which, like the reverse strategy, the portfolio ranking is based on a long-term time horizon. However, the time horizon of their maintenance is like medium-term momentum strategies. Momentarian or momentary strategies are among the combined strategies whose portfolio ranking and stock selection are based on the medium-term time horizon, just like the momentum strategy; however, unlike reverse strategy, they are kept in long term. In this research, an attempt has been made to provide an optimal model for stock selection based on momentum, reverse, and hybrid trading strategies using the GWO algorithm and dynamic panel. Methods: Considering the fact that the purpose of the current research is to answer the questions and test the existing theories in a specific field, it can be categorized as applied research (research and development), and due to its possibility of obtaining a descriptive explanation of a phenomenon, it can be considered as the pseudotype, experiential, descriptive and post-event. In addition, due to description, inference, and problem-solving using quantitative values, it is in the scope of quantitative research. To estimate the model, the information of 175 companies in the period from 2012 to 2021 was used, as well as the software E-Views 12 and MATLAB 2021. Based on the results of 8 time periods of 3, 6, 9, 12, 24, 36, 48, and 60 months, it was analyzed according to different momentum and reverse and combined strategies in loser, winner, and loser-winner, winner-loser positions. It should be noted that two methods of the dynamic panel and gray wolves were used to estimate the strategies. Results: The existence of a momentum strategy was confirmed in the Tehran Stock Exchange, which ensures the hypothesis of underreaction in Iran's capital market. Investors in this market show less reaction to the change of the fundamentals affecting the stock price. Accordingly, the correction of the stock price of these companies is done slowly until it reaches its intrinsic value. Of course, factors such as the volatility limit, the base volume, and the trading node law also fuel this slowness and cause the price correction process to take place with a delay by the formation of buying and selling queues. This helps to use the momentum strategy and obtain abnormal returns in this market. As a result, it can be said that the momentum policy and, naturally, based on the research results, combined approaches cannot create abnormal profits for their investors in the capital market of Iran. Conclusion: Financial market activists and investors are advised to use mixed strategies to improve their buying and selling decisions. Due to the improvement of the results of the gray wolf method compared to the simple panel method, they should use artificial intelligence methods instead of regression methods in the calculations and formation of the optimal portfolio.

CEO compensation remains at the forefront of corporate financial discourse – primarily because of its interconnection with firm performance, growth and survivability. Diverse literature exists on CEO compensation and shareholder return, albeit with different findings and/or disagreements. This paper aims to apply a single independent variable enquiry – the CEO total payment to understand how it might influence shareholder return. Research employs a quantitative approach by using a simple OLS technique with data drawn from a random sample of fifty-six companies listed in the S&P 500 Index. The S&P 500 is a stock market index tracking the stock performance of 500 large companies listed on stock exchanges in the United States. It is one of the most commonly followed equity indices. The OLS result yields a P-value of 0.0001, with a negative regression coefficient, which thus indicates a significant negative relationship between the CEO total payment and shareholder return. The result corroborates some extant research regarding the inability of agency theory to provide an overriding explanation for the CEO pay and return relationship. Further research is therefore encouraged to apply more variables, particularly those that may capture CEO's opportunistic behaviour in future CEO and stock return analysis.

This research aims to get empirical evidence the effect of earnings management in increasing stock return received by investor. Earnings management is an activity to manipulated financial statement. Earnings management can be used to improve company performance when the company has a bad performance or it can be used to maintain company performance. There are 2 earnings management, accrual and real activity manipulation. This research used both to see which one can increase stock return. This research used multiple regression analysis to test the hypothesis and the samples are manufacturing companies listed on Indonesia Stock Exchange from 2017-2019. 86 companies are selected as samples using purposive sampling. The results showed that earnings management is a negative signal for investors. When a negative signal given to investors, it will cause a decrease in stock return received by investor. This research provides an overview of earnings management practice can make investor suffer losses, so that capital market supervisors can increase the monitoring of this manipulation practices.

Given the importance of estimating stock returns, the purpose of this study was to identify the factors affecting stock returns by using the meta-analysis method. Meta-analysis is the main tool for combining results in social and behavioral research. It allows researchers to combine quantitative results of studies, explain the compatibility of results, and achieve a single result. Based on the research background, the impacts of different factors on stock returns were considered. A model of factors affecting stock return is designed in the analysis of empirical studies. This research used the meta-analysis method to comprehensively examine the factors affecting stock returns and assess the different factors that had been examined in various studies over the past years. In a similar research, the researcher had selected the factors affecting stock returns and only tested the selected factors via general categories. However, in this research, a more comprehensive study was conducted to separately examine all the factors whose effects on stock returns had been tested in different studies. Therefore, some of the factors investigated in this research had not been studied in the previous research. Accordingly, a model of factors affecting stock returns was developed. In this research, 422 studies were collected and 102 of them were analyzed. Totally, 153 factors were extracted from these studies and finally, 16 factors were tested. The type of effect size calculated in this study was r. Among the examined factors, earnings per share, operating cash flow, net operating assets, operating earnings, market return, earnings quality, and return on equity had an impact on stock returns. Since the majority of the factors affecting stock returns were related to the financial reports of companies, i.e., their financial status and performance, those factors could be considered to investigate investment opportunities.Keywords: Stock Return, Financial Investment, Fundamental Variables, Financial Ratios, Meta-analysis. IntroductionThe stock return is considered as one of the most important criteria in financial decisions. So far, many studies have been conducted to predict stock returns and provide a comprehensive and reliable model for investors and financial activists. The Capital Asset Pricing Model (CAPM) is one of the most important models in the financial field, especially for estimating stock returns (Murthy et al., 2017; Graham & Harvey, 2001). Although the experimental tests initially confirmed the predictive power of this model regarding the positive linear relationship between systematic risk and stock returns, the results of recent studies indicated that the beta coefficient alone had the power to explain the differences in average stock returns, while other variables were also effective in explaining the differences in stock returns (Fama & French, 1992). Despite examining the effects of various factors, combining the results and presenting a comprehensive model of the factors affecting the stock return, have always been of interest. Meta-analysis methodology, which is the main tool for combining results in social and behavioral research, allows researchers to combine quantitative results of studies (Asgarnezhad Nouri et al., 2016). Therefore, the purpose of this meta-analysis was to expand the pattern of factors affecting the stock returns. Method and DataIn this research, the meta-analysis method was used to comprehensively examine the factors affecting stock returns, as well as the different factors that had been examined in various studies over the past years. In this meta-analysis, 422 studies were collected and 102 of them were analyzed. Totally 153 factors were extracted from these studies and finally, 16 factors were tested. The r effect size was used as the effect size measure, which was calculated following Cohen (1977), Card (2015), and Rosenthal and DiMatteo (2001). FindingsAt the significance level of 1%, the heterogeneity of the effect size of the studies was confirmed. As a result, due to the heterogeneity of the effect size, the model of random effects was used. In addition, the value of the I2 statistic for all the factors was greater than 70, which showed that the heterogeneity of the effect size of the studies was at a high level. In general, among the investigated factors, earnings per share, operating cash flow, net operating assets, operating earnings, market return, earnings quality, and return on equity had an impact on the stock returns. The results of the methods of evaluating publication bias also showed that there was no significant bias in this meta-analysis ContributionIn similar meta-analyses, the researcher had selected the factors affecting stock returns and only tested the selected factors in general categories, while in this research, all the factors whose effects on stock returns had been tested in different studies were separately examined in a more comprehensive study to develop a pattern of factors affecting stock returns. In this meta-analysis, the effects of earnings-to-sales ratio, earnings per share, operating earnings, return on assets, earnings quality, and economic added value on stock returns were investigated, while these factors had not been investigated in similar meta-analyzes. The results showed the positive impact of earnings per share, operating earnings, and earnings quality on stock returns among these factors. Conclusion According to the research results, investors and capital market participants are suggested to pay attention to the variable of earnings per share as one of the influencing factors on the stock market for predicting stock returns. The earnings per share represents the company’s performance in terms of profitability. It is part of the variables of fundamental analysis based on the analytical approach. Among other factors affecting stock returns, we could mention operating cash flow and net operating assets. Therefore, to choose stocks for investment, investors are suggested to examine the company's operations and specifically the items related to the company's cash flow and net operating assets. Market returns were among other factors that affect stock returns. Therefore, it is suggested that investors pay attention to changes in the market yield to estimate the changes in the share value. Based on the research findings, the earnings quality was another factor affecting stock returns. Continuity and reproducibility of earnings, transparency and growing earnings, reflection of the economic reality of the company, etc. were the issues raised about the earnings quality. Hence, the investors are suggested to pay attention to it when examining different stocks. Also, among the financial ratios examined in this research, the return on equity had an impact on the stock return. Therefore, investors are suggested to pay attention to the ratio that is focused on the company's net earnings and shareholders' equity to choose stocks and check their value changes. In general, since the majority of the factors affecting stock returns based on this research were related to the company's financial reports, i.e, the company's financial status and performance, these factors can be considered to investigate investment opportunities.

Investor sentiment is the result of trading behavior and irrational beliefs of investors leading to high volatility and market mispricing. This review aims to study the entire spectrum of articles in the domain of investor sentiment using a bibliometric analysis approach. To this end, the study analyzes a total of 1,919 articles published in the Scopus database between 1979 and 2022. The review uncovers major themes, leading authors, influencing articles, trend topics, top contributing countries, and affiliations. The review shows that the research in the domain of investor sentiment is growing exponentially with an annual growth rate of 15.88%, and the year 2020 witnessed the highest number of scientific productions accounting for 252 (13.68%) total publications. The results display that the USA and China are leading countries in terms of the total contribution and volume of studies from respective authors. The review also reveals that existing research in the field has mainly focused on themes such as market efficiency, asset pricing, stock returns, sentiment analysis, IPO underpricing, overreaction, and volatility, whereas Covid-19 and Bitcoin depicted as emerging themes from recent scholarly works.

This study aims to test and analyze the effect of capital structure, profitability, investment opportunity set, firm value, earnings per share, and dividend policy, on stock returns. Our research uses regression analysis to determine and analyze the influence of independent variables on dependent variables. The objects in this study are companies incorporated in LQ45 for the period 2013 - 2021. The reason for choosing LQ45 is because it is a type of index used to measure the price performance of stocks that have high liquidity and large market capitalization and are supported by good firm fundamentals. The results of the study found that the capital structure with indicators debt to equity ratio has a significant negative effect on stock return. Profitability with indicators return on equity and investment opportunity set with indicators price earnings ratio have a positive and significant effect on stock return. While other findings from our study are firm value with price to book value indicators, profitability from the investor's point of view represented by earning per share indicators, and dividend policy with dividend payout ratio indicators have no effect on stock return. [ABSTRACT FROM AUTHOR]

We use an international sample to test theories predicting an association between operating and financial leverage with stock returns and the value premium. We find evidence that operating and financial leverage are related to stock returns and the value premium across the sampled countries. Results hold after considering the trade‐off between financial and operating leverage and are stronger in North American and European subsamples. Consistent with theory, we find that a country's labor share is positively associated with the value premium. Overall, we present evidence suggesting the value premium reflects compensation for exposure to systematic operating and financing risk. [ABSTRACT FROM AUTHOR]

Marketing scholars commonly use Tobin's Q approximation as a metric of firm performance despite criticism that it might provide false positives for marketing-related research questions. Tobin's Q approximation relies on accounting-based information that commonly undervalues intangibles, thus overstating firms' performance in intangibles, such as marketing, human resources, and research and development. Our research empirically demonstrates and confirms the concerns surrounding Tobin's Q as a firm performance metric in the context of an emerging market. Our analysis of 196 publicly traded non-financial Pakistani firms operating in various sectors over a period of five years shows that marketing spending is positively associated with Tobin's Q. In contrast, results are not significant for the alternative market-based firm performance metric, stock return. Our findings cast further doubts on Tobin's Q's reliability as a firm performance metric in the marketing literature and simultaneously contribute to the ongoing discussion on the appropriate selection and use of metrics by marketing scholars. [ABSTRACT FROM AUTHOR]

Copyright of Muhasebe ve Vergi Uygulamalari Dergisi (MUVU) / Journal of Accounting & Taxation Studies (JATS) is the property of Ankara Serbest Muhasebeci Mali Musavirler Odasi and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The purpose of this study is to obtain empirical evidence for the impact of manager ownership and capital structure on stock returns, mediated by dividend policy. Manager ownership is tested by comparing the size of shares owned by the manager to the total number of shares. The size of the capital structure is tested by the leverage ratio, which represents the company's total debt to equity. A stock's return is measured by comparing the market price at the beginning of the year to the market price at the end of the year. The study population utilizes the consumer goods industry listed on the Indonesian Stock Exchange in 2020-2021 consumer goods industry. A sample of 25 companies was extracted based on the target sampling method. This study proves that management ownership and capital structure influence dividend policy. Management ownership and dividend policy affect stock returns, but capital structure does not. Furthermore, the results of the Sobel test prove that dividend policy does not convey the impact of management ownership and capital structure on stock returns. [ABSTRACT FROM AUTHOR]

This study aims to find out 1) how the level of January Effect, Monday Effect and Weekend Effect on Stock Return; 2) how the Stock Return rate on the IDX30 stock index; 3) How the January Effect, Monday Effect and Weekend Effect affect Stock Return listed on IDX30 for the 2017-2021 period either simultaneously or partially. The sample of this study amounted to 5 listed companies in the banking sector listed in IDX30 for the period February 2022 to July 2022 using the purposive sampling method. The technique to analyze hypotheses is to use Panel Data Regression Analysis, T-Test and F-Test with the help of Microsoft Excel 2019 and EViews 10. The results showed 1) The level of January Effect, Monday Effect and Weekend Effect on Stock Return is much influenced by internal and external factors so that it experiences very significant fluctuations; 2) The Stock Return rate on the IDX30 stock index is very good there is a loss if there are cases that affect the world financial sector; 3) The results of the study partially show that The January Effect and Monday Effect affect Stock Returns while the Weekend Effect does not. While simultaneously the January Effect, Monday Effect and Weekend Effect affect Stock Returns. [ABSTRACT FROM AUTHOR]

This study suggests a new measure of productivity for production factors. Adjustment costs for capital‐intensive firms are higher than for labor‐intensive firms (the differences are systematic). Therefore, higher changes in capital relative to labor will induce higher risk. The capital/labor ratio has been studied extensively. However, the new measure is based on other items, which facilitate the marginal changes in capital and labor, rather than quantities. When the elasticity of capital to labor (ECL) is higher, stock returns are significantly higher as well. This is true both statistically and economically. [ABSTRACT FROM AUTHOR]

This research was conducted to determine the effect of Gross Domestic Product, company value, systematic risk on stock return of the kompas100 listed company. The population of this study were companies listed on the Kompas100 index for the 2017-2020 period, with a total sample of 53 companies based on a purposive sampling technique. This study uses panel data regression analysis with the Fixed Effect Model (FEM) regression model. Classical Assumption Test was adopted to test data validation. The results showed that Gross Domestic Product and systematic risk had a negative effect on stock returns, while firm value had no effect on stock returns, with a coefficient of determination of 74 percent. The findings in this study explain that Gross Domestic Product and Systematic Risk had a negative effect on stock return explained by the investors' behavior in terms of decision-making. They tend to avoid market risk and purchase blue chip stock when it is reached its lowest. While firm value had no effect on stock return due to investors' confidence and the good credibility of Kompas100 Index in sorting 100 stocks. [ABSTRACT FROM AUTHOR]

The author examines whether the direct and indirect sentiment measures are distinct from each other. The author finds that the 2 types of sentiment measures have a relatively low correlation between them. The direct sentiment measures have significant explanatory power on contemporaneous stock returns, whereas the indirect sentiment measures have a lagging effect in such explanatory power. If both sentiment measures are used in a model, one can observe a strong synergistic effect in adjusted R2. One can find that the indirect measures' predictive power on future stock return is remarkably higher than that of the direct measures. Also, the indirect measures are mainly driven by short-term interest rate, whereas stock returns most drive the direct measures. [ABSTRACT FROM AUTHOR]

Recent SEC guidelines enabled many Fortune 500 companies to actively adopt social media, such as Twitter, to disseminate information. In this paper, we analyze the relationship between tweets by corporations and stock returns. Our study used over 1.2 million corporate tweets made by thirty companies in the Dow Jones Industrial Average between April 2013 and July 2020. The shocks from the frequency of corporate tweets can positively impact stock returns and trading volume. We, therefore, examine causality and impulse response between frequency of corporate tweets, stock returns, and changes in trading volume using a vector autoregression model. Our findings indicate that 43 percent of stocks exhibit Granger causality between firm-initiated tweets and changes in trading volume. We find evidence consistent with the attention-induced price pressure hypothesis proposed by Barber and Odean. We observe that a shock in corporate tweeting behavior translates into a positive effect on changes in trading volume and returns in 73 percent and 60 percent of stocks, respectively. These results are significant for developing appropriate social media communication strategies. The findings are also valuable for investors and traders who can deploy forecasting models utilizing corporate tweets to earn superior returns. [ABSTRACT FROM AUTHOR]

The present research paper aims to assess and quantify the downside risk of Euro Area stock markets using the Value at Risk (VaR) methodology over a substantial time frame spanning 26 years. The study employs daily closing price data from the main stock exchanges of Euro Area nations. Using the historical simulation method, VaR estimates are calculated for each country's stock index, providing valuable insights into market performance and risk levels during both normal and crisis periods. The non-parametric nature of the historical simulation approach is favored due to its flexibility in dealing with non-normal distribution data, making it suitable for this analysis. The findings reveal significant variations in downside risk among Euro Area countries. Certain nations consistently exhibit lower VaR estimates, indicating comparatively lower downside volatility and potential losses. These markets may prove attractive to risk-averse investors seeking stability during adverse market conditions. In contrast, some countries consistently demonstrate higher VaR estimates, signaling heightened downside risk, which may offer higher potential returns but may not align with risk-averse investors' preferences. During periods of crisis, certain Euro Area markets display a lower level of downside volatility, showcasing their resilience during turbulent times. This information can guide investors in constructing diversified portfolios that can withstand adverse market conditions. Additionally, policymakers can draw upon these findings to formulate targeted monetary policies to support financial markets during economic uncertainty. Overall, this study contributes valuable insights into downside risk and market performance in Euro Area stock markets, providing investors, policymakers, and financial participants with essential information to make informed decisions and navigate the complexities of global financial markets effectively. [ABSTRACT FROM AUTHOR]

Copyright of Itobiad: Journal of the Human & Social Science Researches / İnsan ve Toplum Bilimleri Araştırmaları Dergisi is the property of Itobiad: Journal of the Human & Social Science Researches and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This research aims to test and analyze information from the cash flow statement on the share return. The cash flow intended is from operating, financing, and investing activities. Meanwhile, the shares utilized belong to the infrastructure, utility, and telecommunication companies listed on the Indonesian capital market between 2018 and 2021. Because this study uses the change in three cash flows, the secondary data from 2017 to 2021 based on the firm annual reports and the stock price at the end of these years are employed. Additionally, the t-statistics and their probability provided by a multiple regression model to statistically examine the hypotheses proposed are applied. Finally, this study concludes that the higher the cash flow from investing activities, the higher the stock return. However, the positive change in the financing cash flow tends to reduce this return. Meanwhile, this return is not affected by the cash flow from operating activities. [ABSTRACT FROM AUTHOR]