Jackknife estimator for tracking error variance of optimal portfolios

Gopal K. Basak, Ravi Jagannathan, Tongshu Ma

Research output: Contribution to journalArticlepeer-review

15 Scopus citations

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&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.

Original languageEnglish (US)
Pages (from-to)990-1002
Number of pages13
JournalManagement Science
Volume55
Issue number6
DOIs
StatePublished - Jun 1 2009

Keywords

  • Jackknife
  • Minimum-risk portfolios
  • Tracking error

ASJC Scopus subject areas

  • Strategy and Management
  • Management Science and Operations Research

Fingerprint Dive into the research topics of 'Jackknife estimator for tracking error variance of optimal portfolios'. Together they form a unique fingerprint.

Cite this