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| Masato Ubukata |
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| ''Large-scale portfolios using realized covariance matrix: evidence from the Japanese stock market'' |
| ( 2010, Vol. 30 No.4 ) |
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| 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. |
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| Keywords: Large-scale portfolio selection, Realized covariance matrix, high-frequency data |
JEL:
C5 - Econometric Modeling: General |
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| Manuscript Received : Sep 15 2010 | | Manuscript Accepted : Nov 08 2010 |
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