Amiya Kumar Mohapatra

This paper investigates five leading equity market anomalies – size, value, momentum, profitability, and asset growth, for four Western European markets, namely, Germany, France, Italy and Spain, from January 2002 to March 2018. The study tests whether these anomalies reverse under different macro-economic uncertainty conditions, and evaluates if strategies based on time diversification can be formed using these equity market anomalies. Market anomalies were tested using four major asset pricing models – the Capital Asset Pricing Model, the Fama-French three-factor model, the Carhart model, and the Fama-French five-factor model. Macro-economic uncertainty was tested using two proxies, namely VIX and default premiums. Time diversified strategies were examined by estimating Sharpe ratios of combined portfolios formed by combining winner univariate portfolios. Value effect in Germany, Size effect in France and Profitability effect in Italy and Spain provide the highest unadjusted returns on long side strategies. No significant reversal of these anomalies was found under different macroeconomic uncertainties. Asset pricing tests show that CAPM works well for Spain and Italy, while Carhart’s model explains returns in Germany. The Fama-French five factor model does not seem to be a good descriptor of asset pricing for data. No suitable model for explaining asset returns is identified for France. Finally, it is observed that some of the equity market anomalies seem to be countercyclical and therefore provide time diversification opportunities. The study has implications for academicians, investors, and policy makers by providing insights for developing profitable investment strategies and highlighting the efficacy of alternative models as performance benchmarks.

This study examines the impact of foreign exchange rate fluctuations on various NSE capitalized indices of India. Five exchange rates were chosen based on trading contracts in the currency derivative segment of NSE. These exchange rates are US Dollar-Indian Rupee (USD/INR), Euro-Indian Rupee (EUR/INR), Great Britain Pound-Indian Rupee (GBP/INR), Chinese Yuan-Indian Rupee (CNY/INR) and Japanese Yen-Indian Rupee (JPY/INR), which are used as a regressor in this study. The data of NSE Nifty large-cap 100, Nifty mid-cap 100 and Nifty small-cap from December 1, 2012 to December 1, 2022 was considered for the study. GARCH (1, 1) model was used to analyze the nexus between exchange rate fluctuations and capitalized indices, and it was further validated by DCC GARCH to evaluate the volatility spillover. The result shows that exchange rate fluctuations have a positive effect on stock market volatility along with a varying degree of incidence on small-cap, mid-cap, and large-cap. DCC α has been found to be significant in USD & GBP for small-cap, and GBP & CNY for mid-cap. On the other hand, USD, Euro, CNY and JPY have a significant impact on the large-cap index in the short-run. Further, it is found that there is long-run spillover effect (DCC β) of exchange rates on all capitalized indices of the Indian stock market, and it is highest in in the large-cap case.

Type of the article: Research Article

Abstract
This study aims to investigate the pooled effects of environmental, social, and governance (ESG) practices on banks’ financial performance (FP) using a random effects model of meta-analysis. In line with the PRISMA guidelines, 52 studies were identified as eligible out of 387 studies for this analysis. After applying the inclusion criteria, i.e., studies that have quantitatively reported the required measures like the correlation coefficient between ESG and FP, 16 studies were considered for meta-analysis with a combined total sample of 4,084 participants. The combined effect size was r = 0.10 (SE = 0.10, 95% CI: –0.11 to 0.31), reflecting a weak and statistically insignificant correlation, displaying no impact of ESG practices on the financial performance of banks from 2018 to 2025. Furthermore, the predicted interval was –1.38 to 1.59, which means that future research would provide very heterogeneous effect sizes. A heterogeneity analysis shows that there is wide variation among the studies (Q = 1213.82, p < 0.001, I² = 98.76%), indicating that differences in study characteristics may lead to differences in effect sizes. The trim and fill method provides no evidence for the existence of missing studies; however, publication bias is considered a possibility. The findings should be interpreted cautiously, given their high heterogeneity and the suspected source of bias. Despite their small effect size, inconsistencies across studies highlight the need for future research to investigate possible moderating factors. Practical implications emphasize that even if the generalizability of the findings is established, it cannot be without considering study-specific variables.

The efficient market hypothesis states that in the efficient markets, participants cannot make extra-normal returns by exploiting any publicly available information. However, traders are constantly looking to exploit publicly available information to generate abnormal returns for themselves and their clients. One such event is share buyback announcement, which traders can utilize to create profitable trading strategies. The authors undertake the present study to examine if share buyback announcements provide profitable trading strategies to traders. Event study methodology has been adopted to analyze buyback announcements by Indian companies from January 2012 to December 2018. Forty-one (41) day window period comprising of 20 days pre-event, an announcement day, and 20 days post-event period is created to analyze the risk-adjusted average abnormal returns. The empirical findings suggest that there are negligible trading opportunities available for investors post announcements. However, significant risk-adjusted returns are found in the pre-event window, indicating that if investors can predict buyback announcements, they may earn extra-normal returns. The study confirms that Indian stock markets are in the semi-strong form of efficiency. The study also provides a profitable trading strategy for investors in the pre-event window. Finally, it also draws the regulators’ attention to see if insider trading could be the reason for abnormal returns in the pre-event window. The authors conclude the results by confirming that Indian markets are semi-strong in market efficiency and by indicating regulatory interventions to control insider trading.

Acknowledgement
The infrastructural support provided by FORE School of Management, New Delhi in completing this paper is gratefully acknowledged.