Influences of macroeconomic variables on Indian stock market volatility: an empirical study

The relationship between macroeconomic variables and stock market performance has attracted considerable attention in financial economics; however, existing evidence for the Indian stock market remains inconclusive, as previous studies have generally relied on a single econometric technique, shorter sample periods, or linear modelling approaches. Consequently, limited evidence is available on how macroeconomic variables simultaneously influence long-run equilibrium, short-run dynamics, asymmetric responses, volatility persistence, and regime-dependent market behaviour, particularly in the post-COVID period. Addressing these methodological, empirical, temporal, and theoretical gaps, this study develops an integrated econometric framework to examine the impact of inflation, crude oil prices, exchange rates, foreign institutional investment (FII), and gold prices on the BSE Sensex using monthly data from 2000–01 to 2024–25. Unlike previous studies, the analysis combines Quantile Regression, Autoregressive Distributed Lag (ARDL) Bounds Testing, Granger Causality Analysis, ARCH, GARCH, EGARCH, and Markov Switching Regression within a unified framework, thereby enabling the simultaneous investigation of long-run relationships, short-run adjustments, nonlinear responses, volatility dynamics, and market regime shifts. The empirical results confirm the existence of a stable long-run cointegrating relationship between the selected macroeconomic variables and the Sensex, with FII emerging as the only statistically significant long-run determinant. Quantile regression reveals that inflation exerts stronger adverse effects during weak market conditions, whereas crude oil prices, gold prices, and FII inflows contribute more positively during bullish market phases. The volatility models confirm significant volatility clustering, persistence, and asymmetric responses to market shocks. At the same time, the Markov Switching Regression identifies distinct bull and bear market regimes, demonstrating that macroeconomic effects vary across market states. By integrating multiple complementary econometric techniques within a single analytical framework, this study extends the literature on emerging financial markets. It provides a more comprehensive understanding of the nonlinear and regime-dependent interactions between macroeconomic fundamentals and stock market performance. The findings offer valuable implications for policymakers, financial regulators, and investors in promoting financial stability, managing market risk, and formulating evidence-based macroeconomic and investment strategies.