An Empirical Analysis of Quantile-Based Volatility Spillovers and Macroeconomic Shocks: Evidence from US and Indian Financial Markets

Abstract

This study examines volatility spillovers and interconnectedness among major financial markets, namely the stock, bond, gold, and crude oil markets, while considering the influence of macroeconomic shocks. To capture differences in market behaviour across various market conditions, the study employs a Quantile Vector Autoregression (QVAR) approach, which allows volatility transmission to be analysed under low, normal, and high volatility regimes. Volatility is derived from return series and Forecast Error Variance Decomposition (FEVD) is used to measure the direction and intensity of spillovers among the markets. The findings show that volatility spillovers are stronger during periods of high market uncertainty. Stock and crude oil markets act as major transmitters of volatility, especially during extreme conditions, while bond and gold markets mainly serve as receivers, with gold displaying safe shaven characteristics during market stress. Macroeconomic shocks, particularly those related to policy uncertainty and geopolitical risk, significantly amplify volatility transmission across markets. These results highlight the importance of considering regime-dependent spillovers and macroeconomic factors in investment decisions and risk management.