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.
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Paper provided by National Bureau of Economic Research, Inc in its series NBER Working Papers with number
10447.
Length: Date of creation: Apr 2004 Date of revision: Handle: RePEc:nbr:nberwo:10447
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Find related papers by JEL classification: G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions G12 - Financial Economics - - General Financial Markets - - - Asset Pricing
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