A model-free measure of aggregate idiosyncratic volatility and the prediction of market returns

René Garcia, Daniel Mantilla-García, Lionel Martellini

Research output: Contribution to journalArticlepeer-review

32 Scopus citations

Abstract

In this paper, we formally show that the cross-sectional variance of stock returns is a consistent and asymptotically efficient estimator for aggregate idiosyncratic volatility. This measure has two key advantages: It is model free and observable at any frequency. Previous approaches have used monthly model-based measures constructed from time series of daily returns. The newly proposed cross-sectional volatility measure is a strong predictor for future returns on the aggregate stock market at the daily frequency. Using the cross section of size and book-to-market portfolios, we show that the portfolios' exposures to the aggregate idiosyncratic volatility risk predict the cross section of expected returns.

Original languageEnglish
Pages (from-to)1133-1165
Number of pages33
JournalJournal of Financial and Quantitative Analysis
Volume49
Issue number5-6
DOIs
StatePublished - 7 Jul 2014
Externally publishedYes

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