Large-scale portfolios using realized covariance matrix: evidence from the Japanese stock market

Masato Ubukata ()
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Masato Ubukata: Department of Economics, Kushiro Public University of Economics

Economics Bulletin, 2010, vol. 30, issue 4, 2906-2919

Abstract: This paper examines effects of realized covariance matrix estimators based on high-frequency data on large-scale minimum-variance equity portfolio optimization. The main results are: (i) the realized covariance matrix estimators yield a lower standard deviation of large-scale portfolio returns than Bayesian shrinkage estimators based on monthly and daily historical returns; (ii) gains to switching to strategies using the realized covariance matrix estimators are higher for an investor with higher relative risk aversion; and (iii) the better portfolio performance of the realized covariance approach implied by ex-post return per unit of risk and switching fees seems to be robust to the level of transaction costs.

Keywords: Large-scale portfolio selection; Realized covariance matrix; high-frequency data (search for similar items in EconPapers)
JEL-codes: C5 G1 (search for similar items in EconPapers)
Date: 2010-11-08
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