A Jackknife Estimator for Tracking Error Variance of Optimal Portfolios Constructed Using Estimated Inputs1

Gopal K. Basak, Ravi Jagannathan and Tongshu Ma

No 10447, NBER Working Papers from National Bureau of Economic Research, Inc

Abstract: We develop a jackknife estimator for the conditional variance of a minimum-tracking- error-variance portfolio constructed using estimated covariances. We empirically evaluate the performance of our estimator using an optimal portfolio of 200 stocks that has the lowest tracking error with respect to the S&P500 benchmark when three years of daily return data are used for estimating covariances. We find that our jackknife estimator provides more precise estimates and suffers less from in-sample optimism when compared to conventional estimators.

JEL-codes: G11 G12 (search for similar items in EconPapers)
Date: 2004-04
New Economics Papers: this item is included in nep-fin
Note: AP
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