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Jackknife Estimator for Tracking Error Variance of Optimal Portfolios

Indian Statistical Institute, Kolkata 700108, India
Northwestern University and NBER, Evanston, Illinois 60208
Binghamton University, Binghamton, New York 13902
gkb{at}isical.ac.in
rjaganna{at}northwestern.edu
tma{at}binghamton.edu

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&P 500 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.

Key Words: jackknife; tracking error; minimum-risk portfolios
History: Received: July 29, 2007; accepted: November 28, 2008.