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This study aims to investigate the association between board diversity and systematic risk. The theoretical framework used in this study is based on agency and resource dependency theories.

Using a panel data set of 788 firms listed in the Morgan Stanley Capital International (MSCI) Emerging Markets index from 2015 to 2020, the authors apply Panel-Corrected Standard Error estimation method to test the three proposed hypotheses and the two-stage least squares method is adopted for the endogenous test.

The results suggest that board-specific skills diversity (BSSD) and board independence (BIND) have a negative impact on systematic risk. On the other hand, board gender diversity does not affect systematic risk. The findings reinforce the relevance of board diversity for reducing systematic risk and offer valuable insights for policymakers and investors, suggesting that the presence of directors with specific skills and independent directors could reduce firms’ systematic risk.

The study extends the scope of agency and resource dependency theories by suggesting that the BSSD and BIND reduce agency costs and bring critical resources to the firm’s survival.

The findings support policymakers and managers in reducing systematic risk. In addition, the results demonstrate the importance of policies that encourage board diversity and BIND.

The study demonstrates how companies can reduce systematic risk through board diversity and BIND.

To the best of our knowledge, this is the first study to investigate the association between board diversity and systematic risk only in emerging markets.

The authors examined whether stocks with higher left-tail risk measures earn higher or lower futures returns. Specifically, the authors estimate the cross-sectional principal component of a battery of left-tail risk measures and analyze future returns on stocks with high principal component values. In contrast to finance theories on the risk–return trade-off relationship, the study results show that high left-tail risk stocks have lower future returns. This finding is robust to various left-tail risk measures and controls for other risk factors. Moreover, the negative relationship between the left-tail risk and returns is more pronounced for stocks that are actively traded by retail investors. This empirical result is consistent with behavioral theory that when investors make decisions based on experience, they tend to underweight the likelihood of rare events.

This study aims to examine the nexus of corporate governance with firms' financial risk-taking behavior under the corporate social responsibility (CSR) disclosures in the context of non-financial listed firms of an emerging economy.

This study investigates the relationship between corporate governance as evaluated by an index and several financial risks, including idiosyncratic, default and systematic risks. The connection of corporate governance with financial risks is also studied while considering the moderation of CSR disclosures. The data are collected from 2014 to 2018 of 73 top 100-index listed non-financial firms of Pakistan Stock Exchange (PSX). Panel regression fixed effect and 2-step generalized method of moments techniques are applied to confirm the hypothesis along with the diagnostic tests to confirm that all outcomes of models must be authentic and reliable.

The study’s findings confirm that enhancing the overall corporate governance measures resulted in an augment in the firm’s risk due to weak control and regulations prevailing in emerging economies. Moreover, CSR disclosures enhance stakeholder information, lessen information asymmetry about management policies and mitigate the risk associated with operational uncertainties.

This study has a practical implementation to policymakers that effective monitoring and controlling measures facilitate the corporate management for minimizing the financial risks. Further, the study’s findings shed light that implementing corporate governance measures is not enough to mitigate financial risks until supervisory measures in the form of CSR disclosures are not taken to analyse corporate governance effectiveness.

This paper enhances the key findings in the literature by examining the role of corporate governance measures with respect to firms’ financial risks considering the moderating role of CSR disclosures. Furthermore, this research adds to the body of knowledge regarding the implementation of monitoring measures that assist in the mitigation of firms’ financial risks hence firm value.

This article aims to systematically review the literature published in recognized journals focused on cognitive heuristic-driven biases and their effect on investment management activities and market efficiency. It also includes some of the research work on the origins and foundations of behavioral finance, and how this has grown substantially to become an established and particular subject of study in its own right. The study also aims to provide future direction to the researchers working in this field.

For doing research synthesis, a systematic literature review (SLR) approach was applied considering research studies published within the time period, i.e. 1970–2021. This study attempted to accomplish a critical review of 176 studies out of 256 studies identified, which were published in reputable journals to synthesize the existing literature in the behavioral finance domain-related explicitly to cognitive heuristic-driven biases and their effect on investment management activities and market efficiency as well as on the origins and foundations of behavioral finance.

This review reveals that investors often use cognitive heuristics to reduce the risk of losses in uncertain situations, but that leads to errors in judgment; as a result, investors make irrational decisions, which may cause the market to overreact or underreact – in both situations, the market becomes inefficient. Overall, the literature demonstrates that there is currently no consensus on the usefulness of cognitive heuristics in the context of investment management activities and market efficiency. Therefore, a lack of consensus about this topic suggests that further studies may bring relevant contributions to the literature. Based on the gaps analysis, three major categories of gaps, namely theoretical and methodological gaps, and contextual gaps, are found, where research is needed.

The skillful understanding and knowledge of the cognitive heuristic-driven biases will help the investors, financial institutions and policymakers to overcome the adverse effect of these behavioral biases in the stock market. This article provides a detailed explanation of cognitive heuristic-driven biases and their influence on investment management activities and market efficiency, which could be very useful for finance practitioners, such as an investor who plays at the stock exchange, a portfolio manager, a financial strategist/advisor in an investment firm, a financial planner, an investment banker, a trader/broker at the stock exchange or a financial analyst. But most importantly, the term also includes all those persons who manage corporate entities and are responsible for making their financial management strategies.

Currently, no recent study exists, which reviews and evaluates the empirical research on cognitive heuristic-driven biases displayed by investors. The current study is original in discussing the role of cognitive heuristic-driven biases in investment management activities and market efficiency as well as the history and foundations of behavioral finance by means of research synthesis. This paper is useful to researchers, academicians, policymakers and those working in the area of behavioral finance in understanding the role that cognitive heuristic plays in investment management activities and market efficiency.

This study aims to examine the performance of environmental, social and governance (ESG) equity indices in Latin America (LA), evaluating their risk-return characteristics in comparison to conventional benchmark indices.

Using a quantitative empirical approach, the authors analyze ESG equity indices from Brazil, Mexico, Chile, Peru and Colombia, employing metrics such as Sharpe, Sortino and Omega ratios to measure risk-adjusted returns. Regression analysis is employed to assess the replicability of ESG indices by benchmark indices. Monte Carlo simulations are conducted to explore the potential increase in risk-adjusted returns when ESG equity indices are incorporated into portfolios.

The study addresses critical questions for investors: Can ESG indices outperform their benchmarks? Can these ESG indices be replicated by benchmark counterparts? Do ESG equity indices enhance portfolio diversification? The findings reveal that investing in ESG indices has the potential to enhance risk-adjusted returns and portfolio diversification.

While this study focuses on various LA economies, it’s important to note variations in currency and volatility.

For investors in LA, this study highlights the importance of considering ESG indices as part of their investment strategies. While not all ESG indices outperform conventional ones, some may improve diversification and risk-adjusted performance. Investors should carefully assess market-specific conditions and national factors when making investment decisions.

The primary contribution of this study is its focus on LA countries in the examination of diverse portfolios. The research provides valuable insights into the performance of ESG indices in this region compared to conventional benchmark indices. This approach addresses an important gap in the existing literature and offers a more comprehensive perspective on ESG investing and portfolio diversification.

Se examina el rendimiento de los índices-ESG en América Latina (AL), evaluando sus características de riesgo y retorno en comparación con los índices convencionales.

Utilizando un enfoque cuantitativo, analizamos los índices-ESG de Brasil, México, Chile, Perú y Colombia, empleando ratios de Sharpe, Sortino y Omega para medir los rendimientos ajustados al riesgo. Se utiliza análisis de regresión para evaluar la replicabilidad de los índices-ESG por parte de los índices de referencia. Se realizan simulaciones de Monte-Carlo para explorar el aumento en los rendimientos ajustados al riesgo cuando se incorporan los índices-ESG en las carteras.

El estudio aborda preguntas críticas: ¿Pueden los índices-ESG superar a sus índices de referencia? ¿Pueden estos índices-ESG ser replicados por sus contrapartes de referencia? ¿Mejoran los índices-ESG la diversificación de las carteras? Los hallazgos revelan que la inversión en índices-ESG tiene el potential de mejorar los rendimientos y la diversificación de las carteras de inversión.

Aunque este estudio se centra en diversas economías de AL, es importante tener en cuenta variaciones en moneda y volatilidad.

La principal contribución de este estudio radica en su enfoque en países de AL en el examen de carteras diversas; ofrece valiosos conocimientos sobre el rendimiento de los índices-ESG en esta región en comparación con los índices convencionales.

The aim of this paper is to systematically review the literature published in recognized journals focused on recognition-based heuristics and their effect on investment management activities and to ascertain some substantial gaps related to them.

For doing research synthesis, systematic literature review approach was applied considering research studies published within the time period, i.e. 1980–2020. This study attempted to accomplish a critical review of 59 studies out of 118 studies identified, which were published in reputable journals to synthesize the existing literature in the behavioural finance domain-related explicitly to recognition-based heuristics and their effect on investment management activities.

The survey and analysis suggest investors consistently rely on the recognition-based heuristic-driven biases when trading stocks, resulting in irrational decisions, and an investment strategy constructed by implementing the recognition-based heuristics, would not result in better returns to investors on a consistent basis. Institutional investors are less likely to be affected by these name-based behavioural biases in comparison to individual investors. However, under the context of ecological rationality, recognition-based heuristics work better and sometimes dominate the classical methods. The research scholars from the behavioural finance community have highlighted that recognition-based heuristics and their impact on investment management activities are high profile areas, needed to be explored further in the field of behavioural finance. The study of recognition-based heuristic-driven biases has been found to be insufficient in the context of emerging economies like Pakistan.

The skilful understanding and knowledge of the recognition-based heuristic-driven biases will help the investors, financial institutions and policy-makers to overcome the adverse effect of these behavioural biases in the stock market. This article provides a detailed explanation of recognition-based heuristic-driven biases and their influence on investment management activities which could be very useful for finance practitioners’ such as investor who plays at the stock exchange, a portfolio manager, a financial strategist/advisor in an investment firm, a financial planner, an investment banker, a trader/ broker at the stock exchange or a financial analyst. But most importantly, the term also includes all those persons who manage corporate entities and are responsible for making its financial management strategies.

Currently, no recent study exists, which reviews and evaluates the empirical research on recognition-based heuristic-driven biases displayed by investors. The current study is original in discussing the role of recognition-based heuristic-driven biases in investment management activities by means of research synthesis. This paper is useful to researchers, academicians, and those working in the area of behavioural finance in understanding the role that recognition-based heuristics plays in investment management activities.

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 paper assesses the co-movement between Pax gold and six fiat currencies. It also investigates the optimal time-varying hedge ratios in order to examine the properties of Pax gold as a diversifier and hedge asset.

This paper examines the volatility spillover between Pax gold and fiat currencies using the framework of wavelet analysis, BEKK-GARCH models and Range DCC-GARCH. Moreover, this paper proposes to use the covariance and variance structure obtained from the new range DCC-GARCH framework to estimate the time-varying optimal hedge ratios, the optimal weighs and the hedging effectiveness.

Wavelet coherence method reveals that, at low frequency, large zone of co-movements appears for the pairs Pax gold/EUR, Pax gold/JPY and Pax gold/RUB. Further, the BEKK results show unidirectional (bidirectional) transmission effects between Pax gold and EUR, GBP, JPY and CNY (INR, RUB) fiat currencies. Moreover, the Range DCC results show that the Pax gold and the fiat currency returns are weakly correlated with low coefficients close to zero. Thus, Pax gold seems to serve as a safe haven asset against the systematic risk of fiat currency markets. In addition, the results of optimal weights show that rational investor should invest more in Pax gold and less in fiat currencies. Concerning the hedge ratios results, the findings reveal that the INR (JPY) fiat currency appears to be the most expensive (cheapest) hedge for the Pax-gold market. However, the JPY’s fiat currency appears to be the cheapest one. As for hedging effectiveness results, the authors found that hedging strategies including fiat currencies–Pax gold pairs are most likely to sharply decrease the portfolio’s risk.

A comprehensive understanding of the relationship between Pax Gold and fiat currencies is crucial for refining portfolio strategies involving cryptocurrencies. This research underscores the significance of grasping volatility transmissions between these currencies, providing valuable insights to guide investors in their decision-making processes. Moreover, it encourages further exploration into the interdependencies of digital currencies. Additionally, this study sheds light on effective contagion risk management, particularly during crises such as Covid-19 and the Russia–Ukraine conflict. It underscores the role of Pax Gold as a safe-haven asset and offers practical guidance for adjusting portfolios across various economic conditions. Ultimately, this research advances our comprehension of Pax Gold’s risk-return profile, positioning it as a potential hedge during periods of uncertainty, thereby contributing to the evolving literature on cryptocurrencies.

This study’s primary value lies in its pioneering empirical examination of the time-varying correlations and scale dependence between Pax Gold and fiat currencies. It goes beyond by determining optimal time-varying hedge ratios through the innovative Range-DCC-GARCH model, originally introduced by Molnár (2016) and distinguished by its incorporation of both low and high prices. Significantly, this analysis unfolds within the unique context of the Covid-19 pandemic and the Russian–Ukrainian conflict, marking a novel contribution to the field.

This study aims to verify the significance of Andersen (2008) corporate risk management (CRM) framework in Asian emerging markets (AEMs) to control firm risk and improve firm performance.

The cross-sectional analyses are performed on a sample of 4,609 firms across nine Asian emerging countries using 2SLS estimation technique.

The empirical findings show that the adoption of CRM not only enhances firm performance by increasing the firm ability to capitalize on the market opportunity but also plays a significant role in reducing firm risk. The findings of this study assert that by institutionalizing risk management practices into an integrated CRM framework, the firm can reap multiple benefits by maintaining better contractual agreements and strategic partnerships with key stakeholders.

The study shifts the focus of CRM away from Western countries toward AEMs, which has been afflicted by high risks and uncertainties. The effectiveness of CRM against firm risk is established by dividing firm risk into firm-specific risk and systematic risk. Furthermore, this study also establishes that CRM not only leads to high returns but also reduces firm operational and production costs. Overall, the study provides a compelling argument to implement CRM for improving organizational performance and managing risks in a strategic and integrated manner. The findings are also relevant to risk management practitioners, as well as to academicians interested in the broader fields of corporate finance and strategy.

The study aims to test prospect theory (PT) predictions in the cryptocurrency (CC) market. It proposes a new asset pricing model that explores the potential of prospect theory value (PTV) as a significant predictor of CC returns.

The study comprehensively analyses a large sample set of 1,629 CCs, representing more than 95% of the CC market. The study uses a portfolio analysis approach, employing univariate and bivariate sorting techniques with equal-weighted and value-weighted portfolios. The study also employs ordinary least squares (OLS) regression, panel data methods and quantile regression (QR) to estimate the models.

This study demonstrates an average inverse relationship between PTV and CC returns. However, this relationship exhibits asymmetry across different quantiles, indicating that investor reactions vary based on market conditions. Moreover, PTV provides more robust predictions for smaller CCs characterized by high volatility and illiquidity. Notably, the findings highlight the dominant role of the probability weighting (PW) component in PT for predicting CC behaviors, suggesting a preference for lottery-like characteristics among CC investors.

The study is one of the early studies on CC price dynamics from the PT perspective. The study is the first to apply a QR approach to analyze the cross-section of CCs using a PT-based asset pricing model. The results shed light on CC investors' decision-making processes and risk perception, offering valuable insights to regulators, policymakers and market participants. From a practical perspective, a trading strategy centered around the PTV effect can be implemented.