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

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

Journal of Financial and Quantitative Analysis, 2014, vol. 49, issue 5-6, 1133-1165

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.

Date: 2014
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Citations: View citations in EconPapers (25)

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Working Paper: A Model-Free Measure of Aggregate Idiosyncratic Volatility and the Prediction of Market Returns (2013) Downloads
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