Jackknife Estimator for Tracking Error Variance of Optimal Portfolios

• 成果类型: Article
• 署名作者: Basak, Gopal K.; Jagannathan, Ravi; Ma, Tongshu
• 署名单位: Indian Statistical Institute; Indian Statistical Institute Kolkata; Northwestern University; National Bureau of Economic Research; State University of New York (SUNY) System; Binghamton University, SUNY
• 刊物名称: MANAGEMENT SCIENCE
• ISSN/ISSBN: 0025-1909
• DOI: 10.1287/mnsc.1090.1001
• 发表日期: 2009
• 页码: 990-1002
• 关键词: jackknife; tracking error; minimum-risk portfolios

摘要

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.