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Investors who can transfer their savings to investments in a well-regulated market benefit not only themselves but also economic development. Hence, it is crucial for fund owners to evaluate their stock market investment decisions. The goal of the study is to understand which model determines the asset returns most efficiently. In this regard, the validity of single and multi-index asset pricing models (capital asset pricing model-CAPM and Fama–French models) has been examined in the Turkish Stock Exchange for 2009–2020, with the quantile regression (QR) approach.

On 18 portfolios comprised of quoted stocks in the Istanbul Stock Exchange 100 (ISE-100/BIST-100), we test the CAPM, the Fama and French three factor model (FF3) and the Fama and French five factor model (FF5). Empirical analyses have been carried out via QR approach regressing the portfolios' average weekly excess returns on risk premium/market factor (Rm-Rf), firm size, book value/market value (B/M), profitability and investments factors. QR estimation has been employed since QR is more effective and provides a better definition of the distribution’s tails.

Our empirical findings have revealed that the average excess weekly returns can be explained more strongly via CAPM. Moreover, Fama and French models are expected to give more reliable result with more data, whereas the market premium would give robust results for the Turkish Capital Market.

Individuals investing in financial assets must find the price model that best fits the market. The return can be approximated in the most appropriate manner using the right variables.

The study differs from other research by comparing the asset pricing models via examining the assets' weekly returns with QR in the Istanbul Stock Exchange 100 (ISE-100).

This study aims to examine the relationship between investor gambling preferences and stock returns, using data for all firms listed in Shanghai A-share market during 2016 and 2021.

This study employs price and trading volume data to capture the behavioral characteristics and gambling preferences of investors. Using the Fama-French three-factor and five-factor models to estimate benchmark returns, this study investigates whether investing in gambling stocks can yield positive excess returns.

The study reveals that stocks identified as gambling stocks generate high returns in the month they are identified as such but subsequently experience a significant drop in excess returns compared to non-gambling stocks over the following one to six months. These results are found to be consistent across different methods used to classify gambling stocks and across various industry sectors.

This research provides insights into the risk-return tradeoff of different stock types and the factors that fuel irrational investment behavior. This research underscores the importance of considering the behavioral elements of investment, particularly in emerging markets where individual investors have a significant impact.

This study advises investors to avoid adopting a gambler or speculative mindset and instead make well-informed and calculated investment decisions that are in line with investors financial objectives and risk appetite. This approach can help create a more stable and sustainable financial market.

This study provides new evidence on the relationship between gambling preferences and future stock returns in financial markets and sheds new light on the important role of irrational factors in investment decisions.

This paper aims to explore the dynamic relationship between ESG scores and REITS returns. The overarching goal is to provide a better understanding of how ESG considerations impact financial performance across different temporal contexts.

Using a sample of 175 European Equity REITs, this analysis combines numerical ESG scores with the Fama-French model, employing both random and fixed effects methods. It integrates individual REIT data and the HESGL (High ESG Scores Minus Low ESG Scores) factors to assess their impact on REIT returns.

The findings highlight divergent patterns between the numerical ESG score and the HESGL factor concerning REIT returns. While the numerical ESG score displays a negative impact in later periods, the HESGL factor demonstrates a positive effect during prosperous times but loses significance during crises.

This research contributes original insights by emphasizing the importance of temporal segmentation in understanding the nuanced and evolving nature of the relationship between ESG scores and REITs’ returns. The study provides a comprehensive analysis and highlights divergent outcomes that are essential for a better interpretation of ESG impacts on real estate investments.

This study aims to examine empirically the nature of supply chain disruptions caused by the COVID-19 pandemic, particularly on the Indian automobile sector.

The authors evaluate the stock market performance of individual company and its quantitative relationship to certain variables related to company’s supply chain.

The authors analysed the company’s operations considering several ratios like asset intensity, company size, labour intensity and inventory to revenue.

The results of analysis can help the companies to understand how disruptions in the supply chain can affect the company’s operations and how it is perceived by the investors in the stock market.

Also, investors are benefitted, as they can understand how different companies with different operational characteristics react to global disruptions in supply chains, which in turn would help them to find better investment opportunities.

Although there is some literature available on the qualitative as well as quantitative analysis, the authors go further to analyse the impact of supply chain disruption on the stocks of the automobile sector.

The detrimental impact of data breaches on organizations and their customers has been well documented in the literature. These breaches expose sensitive information, raising concerns about reputational damage and substantial financial losses for affected firms. Prior research has consistently demonstrated the significant financial repercussions of data breach disclosures, with a significant decline in the market value of breached firms following the incident’s revelation. However, recent literature has documented the shift in consumer perception toward data breaches, warranting a revisit of this important and relevant issue with more recent data. This study aims to revisit the cost of data breach disclosures by empirically analyzing the impact of recent data breach incidents on the market value of affected firms.

The authors collect the data regarding data breach incidents among publicly traded companies in the USA listed in the S&P 500 index from 2013 to 2021. The empirical analysis relies on the event study approach, and the market value of each firm is estimated using the Fama-French three-factor model.

This study finds that the negative market reaction to data breach announcements in recent years has been significantly weaker than those reported in prior works from the past decade. This result confirms the shift in consumer perception toward data breaches in the market.

While prior research has quantified the cost of data breach disclosures, the authors posit that a renewed examination is essential within the contemporary digital environment. Consumer behavior and market sentiment have undergone significant transformations in recent years, necessitating a revisit of this important issue with updated data. This study not only documents this evolving phenomenon but also yields crucial policy recommendations. Notably, it challenges the conventional wisdom to rely on market forces as an adequate deterrent against data breaches. Consequently, updated regulations may be necessary to effectively navigate the complexities of the evolving digital landscape.

The relationship between idiosyncratic risk and stock return has been debated for decades; this study reexamined this relationship in the Pakistani stock market by using the quantile regression approach along with the prospect theory.

The present study is quantitative, and secondary data obtained from an emerging market are used. The quantile regression method allows the estimates of idiosyncratic risk to vary across the entire distribution of stock returns, i.e. the dependent variable. In this study, the standard deviation of regression residuals from the Fama and French three-factor model was used to measure idiosyncratic risk. Convenience sampling is employed; the sample consists of 82 firms listed on the KSE-100 index, with 820 annual observations for the ten years from 2011 to 2020. After computing results by using quantile regression, the study's findings, ordinary least squares (OLS) and least sum of absolute deviation (LAD) regression techniques are also compared.

The quantile regression estimation results indicate that idiosyncratic risk is positively correlated with stock returns and that this relationship is contingent on whether prices are rising or falling. Consistent with the prospect theory, the finding suggests that stock investors tend to avoid risk when they anticipate a loss but are more willing to take risks when they anticipate a profit. The results of the OLS and LAD regressions indicate that the method typically employed in previous studies does not adequately describe the relationship between idiosyncratic risk and stock return at extreme points or across the entire distribution of stock return.

These empirical findings shed new light on the relationship between idiosyncratic risk and stock return in Pakistani stock market literature.

Investigation of the anomalies associated with crashes and jackpots in the Chinese stock market.

We propose a logit model to predict the events of crashes and jackpots in the Chinese stock market. The model introduces a new variable of the price-to-sales ratio and takes into account the market states, Up and Down.

The anomalies associated with crashes and jackpots are not related to variations in economic conditions, but are associated with limits to arbitrage. High-liquidity stocks have strong mispricing effects. The institutions’ speculative trading will push liquid stock prices further away from their fundamentals but avoid buying illiquid stocks with a higher probability of price crashes and jackpots.

We propose a logit model to predict the extreme events of both crash and jackpot in the Chinese stock market. Our model effectively disentangles from CRASHP and JACKP. Compared with the traditional model, it substantially enhances in-sample and out-sample predictions. Based on the predictions of the extreme events, we find two strong and robust pricing effects associated with ex ante CRASHP and JACKP in the Chinese stock market.

We propose an alternative rationale for why some firms employ veterans, driven not solely by benevolence but also by the prospect of enhanced outcomes. Financially, hiring veterans could correlate with improved stock market performance for the hiring company while aligning with corporate social responsibility (CSR) initiatives. Our study centers on the stock market performance of companies hiring veterans. It aims to underscore a lesser-known facet of the veteran employment discourse and its connection to the hiring firm's financial performance.

This paper evaluates the stock market performance of three VETS portfolios (made of companies that hire veterans) compared to the benchmark SPDR S&P 500 ETF. Using a modular approach, we create three VETS passive indices: VETSEW (equal-weighted index), VETSPW (price-weighted index) and VETSVW (value-weighted index). The study analyzes the annual returns, portfolio allocations, risk-adjusted performance metrics and style analysis of the portfolios from January 1, 2020, to December 31, 2022.

The findings indicate that all three VETS portfolios outperformed the benchmark, with higher ending balances and superior risk-adjusted ratios such as the Sharpe and Sortino ratios. Notably, the portfolios demonstrated resilience during challenging periods, including the COVID-19 pandemic, subsequent recovery and an inflationary period.

Limitations include the paper's focus solely on stock returns, suggesting a need for broader financial and management ratios. Moreover, a deeper exploration into how veterans contribute during turbulent times is suggested for further investigation. Although the study touches upon the financial performance of veteran-focused companies during challenging economic times, it does not extensively delve into the specific ways in which veterans add value under such circumstances, presenting an opportunity for further exploration.

Firms that employ veterans amid the COVID-19 pandemic demonstrate favorable risk-adjusted returns, underscoring the potential of veterans as valuable crisis-time assets. Our research further underscores the correlation between veteran hiring and enhanced financial prowess. These insights carry significant policy implications, including CSR initiatives for hiring veterans, skill translation and training and collaboration with veteran organizations.

The paper's findings suggest significant implications: (1) Policymakers could incentivize firms to hire veterans through tax benefits or grants, leveraging their skills for organizational resilience. (2) Collaborative efforts between policymakers and firms can promote responsible hiring, boosting a company's reputation through diversity and inclusion, positively impacting society. (3) Support for skill translation from military to civilian jobs is crucial. Programs certifying skills and tailored education aid veterans' successful transition into the workforce. (4) Collaborations between policymakers, veteran organizations and private sector entities can create networks, job placements and support systems for veterans' employment.

Numerous prior studies within the domain of corporate social responsibility have predominantly neglected the contributions veterans offer to businesses and the underlying reasons behind firms' decisions to employ them. Our research uniquely concentrates on the stock market performance of companies that choose to hire veterans.

After considering the price reversal among countries' indices as a global, coordinated and generalized phenomenon, this paper aims to examine the profitability of the reversal strategy internationally and find an economically essential and predictive reversal effect. Indices' portfolios form based on the prior 48 months; prior losers outperform prior winners by 8.86% per year during the subsequent 48 months. Interestingly, the reversal effect is substantially stronger for emerging countries, yielding 14.04% annually. It remains profitable post-globalization, countering the concern of whether the integration of equity markets synchronized the price reversal worldwide. Returns' differences consistent with portfolio formation approaches are also observed.

This study follows the methodology De Bondt and Thaler (1985) set out and uses the same methodological framework Wouassom et al. (2022) put forward. Nevertheless, this study does not focus on stocks. Still, it employs global equity indices from the viewpoint of an international investor who can switch between worldwide equity indices using a contrarian trading strategy.

My findings indicate that reversal strategies with overlapping portfolios are profitable over the entire sample period and every formation and holding period. These returns are highly statistically significant and vary considerably from one horizon to another. More importantly, the reversal strategies remain, on average, profitable and significant in the period post-1994 but are not particularly distinctive, which implies that the reversal effect survives the globalization impact and indicates that the integration of equity markets together with the international correlation among markets do not synchronize the prices reversal effect around the world given that.

Further work would be recommended to study a more extended period dating back to the nineteenth century or the Victorian Era, characterised by rapid economic development in almost every domain, to verify if reversal is historically compensation for carrying risks exclusively during contraction.

My analysis takes on particular significance given the association between lagged market movement in share prices and investors’ optimism that appears among traders, generating an increasing reversal effect (Siganos and Chelley-Steley, 2006) and has direct implications for predicting and controlling trading costs associated with asset allocation strategies.

The difficulty with using the reversal strategy to uncover the long-term return reversal effects in the equity markets today resides in the fact that the globalization of the economy has fuelled the concentration of assets within institutional investors. The critical insight is that the concentration of equity in the hands of institutional investors activated international equity trading. These institutional investors seek to maximize their shareholder value from the opportunity by simultaneously dealing in many markets while constructing and holding portfolios that include assets from various countries using highly profitable investment strategies such as reversal.

To the best of the authors’ knowledge, this is the first paper to show an easily implemented contrarian strategy that switches back and forth between country indices and generates extraordinarily high abnormal returns of more than 8.86% per annum. We also show that these returns compensate for global risks and for investors ready to take them during contraction.

In the present study, we investigate whether enhanced momentum strategies outperform price momentum strategies and if they show greater resilience and stability under adverse market conditions. We also examine if such strategies are explained by prominent asset pricing models or are a result of behavioral mispricing.

Data consist of the equity shares of all companies listed on National Stock Exchange over the study period. To check the efficacy of enhanced momentum over price momentum, six momentum strategies have been designed and their raw as well as risk-adjusted returns using multi-factor models have been observed. Behavioral mispricing has been examined by constructing an investor attention index. Finally, few robustness tests have been performed to confirm the results.

We find that an enhanced momentum strategy which combines relative and absolute strength momentum outperforms conventional price momentum strategy in India. We also demonstrate that rational pricing models are not able to explain momentum profits for any of the strategies. Finally, we observe that investor overreaction is the possible explanation of momentum profits in India. Thus, our results confirm the role of behavioral mispricing in explaining momentum returns.

Our research is the first major attempt to study enhanced momentum strategies in the Indian context. We experiment with several new enhanced momentum strategies which have not been explored in prior literature. The findings have strong implications for global portfolio managers who wish to design profitable trading strategies.