Correlated Idiosyncratic Volatility Shocks
33 Pages Posted: 24 Aug 2016 Last revised: 9 Jan 2019
Date Written: August 17, 2016
Commonality in idiosyncratic volatility cannot be completely explained by time-varying volatility. We decompose the common factor in idiosyncratic volatility (CIV) of Herskovic et al. (2016) into two components: idiosyncratic volatility innovations (VIN) and time-varying
idiosyncratic volatility (TVV). VIN is priced in the cross section of stock returns, whereas TVV is weakly priced. A long-short strategy based on double-sorted VIN and TVV portfolios earns average returns of 8.0% per year. To capture the commonality in idiosyncratic volatility, we propose the Dynamic Factor Correlation model, which outperforms Engle’s (2002) DCC model in simulations and empirical tests.
Keywords: volatility, GARCH, cross section, stock returns, idiosyncratic risk
JEL Classification: C58, G12, G17
Suggested Citation: Suggested Citation