A Model-Free Measure of Aggregate Idiosyncratic Volatility and the Prediction of Market Returns

René Garcia, Daniel Mantilla-Garcia and Lionel Martellini
Authors registered in the RePEc Author Service: Daniel Mantilla Garcia ()

CIRANO Working Papers from CIRANO

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.

Keywords: Aggregate idiosyncratic volatility; cross-sectional dispersion; prediction of market returns (search for similar items in EconPapers)
Date: 2013-01-01
New Economics Papers: this item is included in nep-ecm, nep-ets, nep-for, nep-mst and nep-rmg
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (5)

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Journal Article: A Model-Free Measure of Aggregate Idiosyncratic Volatility and the Prediction of Market Returns (2014)
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Persistent link: https://EconPapers.repec.org/RePEc:cir:cirwor:2013s-01

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