Evaluating The Asymmetric Effects of Global Geopolitical Risk and Exchange Rate Fluctuations on The NSE NIFTY 50 INDEX: A Time-series Analysis

Abstract

In an era of global financial integration, emerging economies are increasingly exposed to external geopolitical uncertainties and currency fluctuations. The abrupt shifts in global geopolitical environments and exchange rate movements frequently alter domestic capital market mechanisms, inducing unexpected fluctuations in equity return dynamics. The present study examines the asymmetric impacts of global geopolitical uncertainties and USD/INR fluctuations on the Indian equity market, specifically on the benchmark NSE Nifty50Index. Utilising a daily dataset of 2452 observations spanning June6, 2016 to June8, 2026, the paper applied an ML-EGARCH modelling framework under a Generalised Error Distribution (GED) specification by employing the EViews12 software to statistically evaluate how external geopolitical risks and USD/INR exchange rate returns affect domestic equity returns. The models yielded an acceptable model fit for the daily time-series data, with an Adjusted R-squared of 8.00% for aggregate GPR model and 7.96% for disaggregated GPR model. Findings demonstrated that R_USD_INR exhibited strong statistically significant negative relationship (coefficient -0.637307, p-value0.0000 for aggregate GPR model; coefficient -0.635072, p-value0.0000 for disaggregated GPR model; both significant at 1% level) with R_NIFTY. From aggregate GPR regression model, GPR_TOTAL demonstrated significant negative but negligible relationship with R_NIFTY (coefficient -0.000621, p-value0.0097; significant at 1% level). From disaggregated GPR regression model, GPR_THREATS demonstrated weak, negative, marginally significant relationship with R_NIFTY (coefficient -0.000358, p-value0.0791, significant at 10% level) and GPR_ACTIONS demonstrated insignificant relationship with R_NIFTY (coefficient -0.000275, p-value0.1834). Furthermore, the variance equation estimations for both models confirmed highly significant ARCH and GARCH parameters alongwith a negative, statistically significant asymmetry coefficient (p-value0.0000), confirming the presence of significant leverage effects, where negative shocks trigger greater volatility than positive shocks. Consequently, these empirical insights highlight the vulnerabilities inherent in the Indian equity market, necessitating the implementation of advanced derivative-based hedging frameworks.

Keywords