Revisiting the Idiosyncratic Volatility Puzzle in an Emerging Market: New Evidence from India
Author(s):
Jyoti Kumari
Article history:
Received: October 2025
Accepted: 25 March 2026
Abstract:
This study re-examines the idiosyncratic volatility (IVOL) puzzle in an emerging market setting by investigating whether firm-specific risk is systematically priced in the cross-section of Indian equity returns. Using a comprehensive panel of 1,356 non-financial firms listed on the National Stock Exchange over 2000–2024, we implement a dual-measurement framework that distinguishes between unconditional IVOL, derived from a liquidity-augmented multifactor model, and conditional IVOL, estimated via an EGARCH specification to capture time-varying volatility dynamics. Employing both portfolio-sorting techniques and Fama–MacBeth regressions, we document a robust and economically significant positive IVOL–return relation, with substantially stronger pricing effects for conditional IVOL. These findings stand in contrast to the negative IVOL anomaly reported for developed markets and instead support theoretical models of incomplete diversification, limits to arbitrage, and behavioral mispricing in segmented markets. Further, we show that conventional factor models fail to subsume the predictive content of IVOL, particularly when volatility dynamics are explicitly modeled. The results suggest that idiosyncratic volatility in India proxies for a state-dependent, priced risk factor rather than diversifiable noise. Our findings contribute to the asset pricing literature by reconciling conflicting IVOL evidence through a unified framework and by highlighting the critical role of market frictions and conditional risk structures in emerging economies.
Keywords:
Idiosyncratic Volatility; Asset Pricing; Emerging Markets; EGARCH; Fama–MacBeth Regression; Liquidity
Risk; Market Frictions; India
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