All Rights Reserved
AccessEcon LLC 2006, 2008.
Powered by MinhViet JSC
ralph lauren polo

 
Masato Ubukata
 
''Large-scale portfolios using realized covariance matrix: evidence from the Japanese stock market''
( 2010, Vol. 30 No.4 )
 
 
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
JEL: G1 - General Financial Markets: General (includes Measurement and Data)
C5 - Econometric Modeling: General
 
Manuscript Received : Sep 15 2010 Manuscript Accepted : Nov 08 2010

  This abstract has been downloaded 281 times                The Full PDF of this paper has been downloaded 87722 times