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

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  • Garcia, René
  • Mantilla-García, Daniel
  • Martellini, Lionel

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.

Suggested Citation

  • Garcia, René & Mantilla-García, Daniel & Martellini, Lionel, 2014. "A Model-Free Measure of Aggregate Idiosyncratic Volatility and the Prediction of Market Returns," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 49(5-6), pages 1133-1165, December.
    • Handle: RePEc:cup:jfinqa:v:49:y:2014:i:5-6:p:1133-1165_00
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