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

  • René Garcia
  • Daniel Mantilla-Garcia
  • Lionel Martellini

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.

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File URL: http://www.cirano.qc.ca/files/publications/2013s-01.pdf
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Paper provided by CIRANO in its series CIRANO Working Papers with number 2013s-01.

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Length: 58 pages
Date of creation: 01 Jan 2013
Date of revision:
Handle: RePEc:cir:cirwor:2013s-01
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