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This study investigates the efficiency of value relevance and faithful representation when stock market price derivates from its firm value to the investigated IT companies listed in FTSE Taiwan 50. The empirical investigation reveals one financial indicators: Return on equity (ROE) has explanatory ability among seven financial indicators, earnings per share (EPS), book value (BV), dividend yield (Div.), price–earnings ratio (P/E), ROE, return on assets (ROA), and return on operating asset (ROOA) to both sampled companies, United Microelectronics Corporation, UMC, (2303) and Taiwan Semiconductor Manufacturing Company Limited, TSMC, (2330). Furthermore, the empirical results indicate that the higher order moments, skewness and kurtosis, of price deviation do not provide a reliable prediction or explanatory power for stock price trends.

This study aims to investigate the variation in overvaluation proxies and volatility across industry sectors and time.

Using industry sector data from the S&P Capital IQ database, this study applies traditional cross-sectional regressions to investigate the relationship between overvaluation and volatility over the 2001–2020 time period.

This study finds that the most volatile industry sectors generally do not coincide with overvalued industry sectors in the cross-section, implying that there are limitations to price-multiple methods for forecasting future volatility. Rather, this study finds that historical volatility significantly increases the goodness-of-fit when modeling volatility in the cross section of industry sectors. The findings of this study imply that firms should increase disclosures and transparency about corporate practices to decrease downside risk that stems from bad news. In addition, the findings underline the consistency between market efficiency and high levels of volatility in periods of significant uncertainty.

This study proposes a novel approach to examining the cross section of volatility across time for industry sectors.

This study aims to find the relationship of stock market returns and selected financial market variables (market capitalization, earnings per share, price-earnings multiples, dividend yield and trading volume) of Malaysia grounded by the arbitrage pricing theories.

This study empirically examines the effects of selected financial market variables on stock market returns using 64 companies listed in Malaysia's stock market with data spanning from 2005 to 2018. A systematic empirical study based on the Generalized Method of Moments following Arellano and Bond (1991) has been taken to estimate the effect.

The regression result of the financial market variables and stock market return shows that, except for trading volume, all selected financial market variables play significant roles in the stock market returns. Furthermore, market capitalization, earnings per share, price-earnings ratio, dividend yield and trading volume have a positive impact on stock market returns.

The outcome of this study can contribute by helping domestic and global investors devise strategies to minimize their risks. Also, policy administrators can use the outcomes of this study to inform the micro- and macro-level policy formulation.

This study will contribute to filling the gap in knowledge concerning the new release of factors affecting the stock market returns of Malaysia.

Factor investment is booming in global asset management, especially environmental, social, and governance (ESG), dividend yield, and volatility factors. In this chapter, we use data from the US securities market from 2003 to 2019 to predict dividends and volatility factors through machine learning and historical data–based methods. After that, we utilize particle swarm optimization to construct the Markowitz portfolio with limits on the number of assets and weight restrictions. The empirical results show that that the prediction ability using XGBoost is superior to the historical factor investment method. Moreover, the investment performance of our portfolio with ESG, high-yield, and low-volatility factors outperforms baseline methods, especially the S&P 500 ETF.

According to the Association of Certified Fraud Examiners, financial statement fraud represents the smallest amount of fraud cases but results in the greatest monetary loss. The researcher previously investigated the characteristics of financial statement fraud and determined the presence of 16 fraud indicators. The purpose of this study is to establish whether investors and other stakeholders can detect and identify financial statement fraud using these characteristics in an analysis of a company’s annual report.

This study analyses a financial statement fraud case, using the same techniques that were previously applied, including horizontal, vertical and ratio analysis. These are preferred because stakeholders have relatively easy access to them.

The findings show several fraud characteristics, with a few additional ones not previously found prevalent. Financial statement fraud thus tends to differ between cases. It is also easier to detect and identify fraud indicators ex post facto.

This study is a practical case showing that financial statement fraud can be detected and identified in the financial statements of companies that commit fraud.

Investment decisions hold immense significance for investors and eventually affect their portfolio performance. Investors are advised to weigh the costs and benefits associated with every decision in order to make rational investment decisions. However, behavioral finance research reveals that investors' choices often stem from a blend of economic, psychological and sociological factors, leading to irrationality. Moreover, environmental, social and corporate governance (ESG) factors, aligned with behavioral finance hypotheses, also sway opinions and stock prices. Hence, this study aims to identify how individual equity investors prioritize key determinants of investment decisions in the Indian stock market.

The current research gathered data from 391 individual equity investors through a structured questionnaire. Thereafter, a fuzzy analytic hierarchy process (F-AHP) was used to meet the purpose of the research.

Information availability, representative heuristics belonging to psychological factors and macroeconomic indicators falling under economic factors were discovered to be the three most prioritized criteria, whereas environmental issues within the realm of ESG factors, recommendations of brokers or investment consultants of sociological factors, and social issues belonging to ESG factors were found to be the least prioritized criteria, respectively.

Only active and experienced individual equity investors were surveyed in this study. Furthermore, with a sample size of 391 participants, the study was confined to individual equity investors in one nation, India.

This research has implications for individual investors, institutional investors, market regulators, corporations, financial advisors, portfolio managers, policymakers and society as a whole.

To the best of the authors' knowledge, no real attempt has been made to comprehend how active and experienced individual investors prioritize critical determinants of investment decisions by taking economic, psychological, sociological and ESG factors collectively under consideration.

This study examines the influence of the ownership structure of banks on investors' behavior by dissecting the investors' response to news regarding performance indicators in private and government-owned banks.

The event study methodology is used for the analysis. The data for 35 banks (out of 38), listed on the National Stock Exchange (NSE) for a duration of 230 months (January 2001 to February 2020) is collected. A set of cross-sectional regression analyses is done to identify variables influencing the returns under differential circumstances.

Private banks seem to display a sharper response to negative changes in earnings, while government-owned banks show a more robust reaction to a positive change. The contrast is seen in the variables, having a bearing on the abnormal returns After controlling for a set of factors, the regression analysis shows the ownership structure may not matter on abnormal returns (on event day), the factors such as a change in quarterly earnings, firm-size and three-year average-sales growth influence the positive and negative changes in abnormal returns of government banks, and predictability for private banks is found to be poor regarding selected indicators.

The study evaluates the role of ownership structure on the heterogeneity in investors' responses to the financial performance of banks, thereby assisting in designing strategies to ensure the optimal outcome around the quarterly earnings announcements.

The current chapter deals with the environmental, social, and governance (ESG) integration issue that should contribute to the higher expected investment returns as different kinds of risk are managed in a better and more sufficient way. The goal is to study the ESG risks integration into the decision-making process and test the results. The research chapter intends to contribute to the existing discussion by evaluating some integration techniques. Following the development of the European Taxonomy, one can expect increased interest in integrating ESG risks into the financial forecast and asset valuation. The current chapter deals with Berger and UniCredit Bank’s (2010) proposal to include the ESG data as factors influencing the foretasted financial data in terms of direct costs (like energy, waste, water, and paper expenses; payments for sick leaves and employees’ turnover costs); externality costs (like CO₂ compliance costs) and opportunity costs (ESG provisions; expenses for board compensations). The chapter provides an overview of some integration approaches and discusses the idea of incorporating the ESG criteria into the stock valuation and portfolio management process. It is evident that the classical value investing approach is no more suitable. Nevertheless, the tested sample does not show significantly different results based on the backtesting. The research results could be interesting for authors preparing research on the field of sustainability and risk management as well as for portfolio managers considering the ESG integration to achieve the positive alpha.

This study aims to investigate the impact of pollution control bonds (PCBs) on overinvestment within utility firms.

This empirical study analyzes a data set comprising 215 US energy firms observed from 2011 to 2021, using the ordinary least square regression with standard errors adjusted for firm-level clustering.

The study reveals a negative relationship between PCBs and overinvestment, indicating that PCBs are an effective tool in curbing excessive investment. Additionally, it demonstrates that chief executive officer (CEO) overconfidence diminishes the influence of PCBs on overinvestment. These findings remain robust across various metrics for measuring overinvestment and CEO overconfidence, as well as when alternative estimation methods are used. These results align with insights derived from agency theory and upper echelon theories.

Regulators are encouraged to actively promote the use of PCBs as a financing tool for environmentally focused initiatives. To achieve this, regulatory bodies should enhance their presence within the utility sector, particularly in regions grappling with higher pollution levels. This requires the implementation of strategic policies and regulatory frameworks aimed at mitigating excessive investments. Simultaneously, policymakers should take proactive measures to introduce financial instruments designed to optimize investment efficiency, thus facilitating eco-friendly projects.

To the best of the authors’ knowledge, this paper holds the distinction of being the first to examine the impact of a specific type of green bond, namely, PCBs, on overinvestment. Furthermore, it contributes to the literature on personality traits, particularly within the context of the upper echelon theory, by investigating the moderating influence of CEO overconfidence.

This paper discusses whether institutional investors change the shareholding ratio of listed companies through research meeting, and whether this active investment mode can really improve the investment efficiency of institutional investors.

Using empirical research method, this study designs and conducts an empirical research according to empirical research's basic norms. Thus, we acquire needed and credible empirical data. This study analyzes whether institutional investors seek their private interest in researched companies by analyzing their research meetings and the shareholding ratios of different types of institutional investors using Shenzhen Stock Exchange data on listed firms from 2014 to 2018.

This study finds that the research meetings of institutional investors provide participants with reliable information which supports the decision of institutional investors to change their shareholding ratio. The stock price growth rate strengthens the positive correlation between the research meetings of institutional investors and the shareholding ratio of institutional investors. Additionally, transactional institutional investors increase the shareholding ratio, while holding institutional investors do not.

This paper combines the behavior of institutional investors with the holding status of institutional investors, and discusses the impact of institutional investors' behavior on investment decisions. At the same time, it classifies the institutional investors and discusses the attitude of different types of institutional investors towards this active investment mode.