This study aims at examining the short-run and long-run dynamic linkages among exchange rates and stock market index in India through a structured cointegration and Granger causality tests. Daily exchange rates of USD, EUR, CNY, JPY, and GBP to INR along with the daily movement of NSE NIFTY for a period spanning 13 years from 6 September 2005 to 31 December 2018 were used for the analysis. The results reveal that there is no evidence for a stable long-run relationship between NSE NIFTY and the exchange rates under study. However, the VAR-based Granger causality test shows that USD, JPY, and CNY have short-run causal relationship with NSE NIFTY. The NSE NIFTY also seemed to have an influence on USD expressed in terms of Indian rupee. The impulse response analysis further supports the results of the Granger causality test and provides information on the time required for the NSE NIFTY index to recover from a shock caused by the fluctuation in exchange rates.

The recent war between Ukraine and Russia is yet another instance that emphasizes that economic overdependence may destroy the economic fabric of a nation. Taking this premise into consideration, this study aims to examine the long-term and short-term connection between the European Union and the United States GDP growth rates using tools like linear regression, Granger causality test, and impulse response function. Quarterly GDP figures of the European Union and the United States were taken for the period spanning 22 years, starting from quarter 2 of the financial year 1998-1999 to quarter 4 of the financial year 2018-2019. The Regression model and the Granger Causality test prove that the United States’ GDP growth rate is influenced by that of the European Union in the short-run as well as in the long-run, but the EU’s GDP is independent and does not follow the former. The possible explanation can be the trade surplus of the European Union over the United States in the recent past. Hence, the authors are of the opinion that a much more balanced trade between these two powerful economies would ensure the stabilization of the global trade and stability of the global power equation.

This article introduces the Derived Unsystematic Risk Performance Index (DURPIN) as a complementary diagnostic measure for evaluating excess return generated per unit of estimated unsystematic risk. Conventional performance measures such as the Sharpe Ratio, Treynor Ratio, and Jensen’s Alpha provide important insights into total-risk-adjusted, systematic-risk-adjusted, and abnormal return-based performance. Similarly, the Appraisal Ratio relates alpha to residual or non-systematic risk. However, many individual investors and financial advisors deal with concentrated equity positions where firm-specific risk is not fully diversified away in practice. DURPIN is proposed to address this practical setting by relating realized excess return, measured as stock return minus the risk-free rate, to the estimated unsystematic-risk component of the stock. The study applies DURPIN to selected Indian and US stocks to illustrate how the measure may complement established performance ratios in evaluating firm-specific risk-return efficiency across normal and crisis-related market conditions. The findings suggest that DURPIN may provide useful additional insight for retail investors, financial advisors, sectoral portfolios, thematic investments, and concentrated equity holdings. The paper positions DURPIN not as a replacement for existing models but as a simple practitioner-oriented tool for interpreting excess return relative to unsystematic risk actually retained by investors.

This study examines the short-term volatility spillovers and long-term integration between the NASDAQ, CSI 300, and Nifty 50 using EGARCH-X and Johansen Cointegration. The EGARCH-X model is used to analyze the asymmetries and event-driven shocks, while Cointegration tests assess persistent linkages across markets. Daily closing prices from November 2023 to November 2024 and the monthly prices from November 2014 to November 2024 were used for the study. Results indicate that return spillovers from the U.S. and Chinese markets to India are statistically insignificant, but volatility transmissions are significant, with adverse shocks enhancing volatility more than positive ones. These volatility shocks are of short duration, showing the resilience of the Indian stock market. Long-run analysis shows that the absence of Cointegration suggests that the equity market of India functions independently of the U.S. and Chinese markets. This reflects the influence of strong domestic fundamentals and institutional structures. This study contributes to the literature on emerging resilience and integration by distinguishing between return and volatility spillovers. The findings offer insights for investors designing diversification strategies, regulators concerned with risk management, and policymakers evaluating India’s role in the global financial system.