Name: M K Lodi & Mithil Udupa
Country: India

Year: 2026
Volume: Volume No: 13, Issue No: 1, Year: 2026
Page Number: 238-246
DOI: https://doi.org/10.5281/zenodo.19659712

ABSTRACT
This study investigates whether India Volatility Index (India VIX) can serve as an effective
timing indicator for volatility-driven sector rotation in the Indian equity market. Using daily data spanning 2009–2024 across eleven NSE sectoral indices, we employ fixed-effects panel regression, Vector Autoregression (VAR), Granger causality tests, and back-testing within a regime-classification framework. India VIX exhibits a statistically significant inverse relationship with sectoral returns (β = −0.00063, p < 0.01), a result that persists after controlling for the policy interest rate. Granger causality tests establish a unidirectional predictive relationship: India VIX leads sectoral returns, not the reverse. Regime-based analysis reveals that cyclical sectors (Banking, Auto) outperform during low-volatility environments (VIX < 15), while defensive sectors (Pharma, FMCG) provide relative resilience when fear spikes (VIX > 25). A rules-based sector rotation strategy exploiting these regime-dependent patterns achieves a Sharpe ratio of 0.2987 versus 0.1142 for an equal-weighted passive benchmark—a 161.6% improvement—with particularly pronounced outperformance during the COVID-19 crisis and post-crisis recovery. The findings challenge the semi- strong form of market efficiency in an emerging-market context and offer a transparent, implementable framework
for volatility-conscious sector allocation.

Keywords: India VIX; Sector Rotation; Volatility Regimes; Risk-Adjusted Returns;
Emerging Markets; Panel Regression; Granger Causality