Dynamic Hedging and Risk Optimization: Evidence from Sectoral Indices in the Indian Stock Market

The primary focus of this study is to examine how shocks and volatility are transmitted across sector indices in the Indian stock market. This study employs a dynamic conditional correlation generalized autoregressive conditional heteroscedasticity (DCC-GARCH) model, utilizing daily data from five prominent sectoral indices of the National Stock Exchange (NSE) in India, from 1 January 2016 to 31 May 2024. The study shows that sectoral volatility responds very differently across pre-COVID, COVID, post-COVID and geopolitical-crisis periods, with pro-cyclic sectors displaying sharper shock sensitivity during the pandemic and defensive sectors showing stronger stability under geopolitical stress. Consumer durables and financial services consistently provide the strongest hedging benefits during COVID and post-COVID periods, while IT-linked pairs exhibit weak hedging relationships throughout. The geopolitical shock generates volatility but does not compress sector movements as strongly as the pandemic, resulting in shallower and less persistent spillovers. Dynamic hedge ratios and portfolio weights reveal that IT becomes more relevant only in the post-COVID phase, but it does not function as a strong hedge during crisis-driven volatility. Crisis conditions tend to compress diversification opportunities by increasing correlations and connectedness, requiring more careful portfolio rebalancing. These findings offer new insights into how sector-specific behaviours and hedging performance evolve under varying macro-financial conditions, contributing to adaptive risk-management and portfolio-optimization strategies.