Aditya Prasad Sahoo

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 insignificant correlation, and hence displaying no impact of ESG practices on the financial performance of banks during the study period 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.

Type of the article: Research Article

Abstract
This study examines the impact of exchange rate fluctuations on banking and financial service indices in India. To validate this, five exchange rates are considered based on their relative share in the total foreign remittance inflows to India, viz., Arabian Dirham (AED/INR), Great Britain Pound (GBP/INR), Saudi Riyal (SAR/INR), Singapore Dollar (SGD/INR), and US Dollar (USD/INR). The study includes daily data of a decade (2015–2025), and employs various econometric techniques such as ADF test, Johansen cointegration, Vector Error Correction Model (VECM), and Impulse Response Function (IRF) for the analysis. The Johansen cointegration test indicates a long-run relationship between exchange rates and both the sectoral indices, as the probabilities are less than 0.05. The VECM analysis for both the Nifty Bank and Nifty FinServ identified USD/INR (2,308.66; 2,257.58) and SAR/INR (373.25; 360.73) as the dominant long-term drivers, whereas AED/INR (–2,671.406; –2,608.011) acts as a persistent structural anchor with a negative influence. In the short run, shocks in USD/INR and SGD/INR generate immediate positive effects, whereas volatility in AED/INR and SAR/INR leads to temporary negative deviations before the system converges back to the equilibrium. The impulse response function indicates that exchange rate shocks have temporary effects on both the indices, which dissipate quickly, reflecting rapid market adjustment and overall efficiency. The findings of this study will help policymakers to improve the exchange rate risk monitoring system and executives in banks and financial institutions to formulate their hedging strategies. For investors and portfolio managers, the findings suggest that currency movements can serve as early indicators of market fluctuations, thereby supporting more informed investment decisions.