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Estimation risk in covariance

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  • David D Cho

    (Huizenga School of Business, Nova Southeastern University)

Abstract

This article investigates the estimation risk in covariance. Although previous research has shown that the covariance can be estimated accurately by assuming independently and identically distributed normal returns, time-varying volatility and non-normality can lead to imprecise covariance estimates, which can cause economic loss to a mean variance investor. Applying the Fama-French three-factor model to 25 portfolios sorted by size and book-to-market ratio from 1963 to 2008, we find that the estimation risk in covariance is as large as two-thirds of that in the expected return.

Suggested Citation

  • David D Cho, 2011. "Estimation risk in covariance," Journal of Asset Management, Palgrave Macmillan, vol. 12(4), pages 248-259, September.
    • Handle: RePEc:pal:assmgt:v:12:y:2011:i:4:d:10.1057_jam.2011.14
    DOI: 10.1057/jam.2011.14
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    Cited by:

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    2. Platanakis, Emmanouil & Sakkas, Athanasios & Sutcliffe, Charles, 2019. "Harmful diversification: Evidence from alternative investments," The British Accounting Review, Elsevier, vol. 51(1), pages 1-23.
    3. Kazak, Ekaterina & Pohlmeier, Winfried, 2019. "Testing out-of-sample portfolio performance," International Journal of Forecasting, Elsevier, vol. 35(2), pages 540-554.

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