Portfolio Turnover when IC is Time Varying

27 Pages Posted: 13 Feb 2018 Last revised: 28 May 2019

See all articles by Zhuanxin Ding

Zhuanxin Ding

Analytic Investors

Doug Martin

University of Washington

Chaojun Yang

Shanghai Jiao Tong University (SJTU)

Date Written: May 24, 2019

Abstract

We develop new formulas for the turnover and leverage of mean-variance optimal long-short market neutral portfolios, where active weights are obtained using a factor model conditional mean forecast, and a conditional forecast error covariance matrix that reflects strategy risk. We show that for eight commonly used quantitative factors, the turnovers and leverages derived using our long-short formulas are quite close to what the practitioners actually implement. We further carry out extensive simulations for long-only active portfolios and develop a highly accurate empirical formula that relates long-only turnover to long-short turnover, a transfer coefficient, portfolio target tracking error, strategy risk, and a benchmark choice coefficient. Our result shows that when the proper risk model is used in factor investing, the optimal portfolio’s turnover and leverage are well within reasonable practically implementable ranges even if no additional constraints are imposed.

Keywords: turnover, leverage, factor model, conditional mean forecast, conditional forecast error covariance matrix, transfer coefficient, fundamental law of active management

JEL Classification: G, C1, C2, C6

Suggested Citation

Ding, Zhuanxin and Martin, R. Douglas and Yang, Chaojun, Portfolio Turnover when IC is Time Varying (May 24, 2019). Available at SSRN: https://ssrn.com/abstract=3117881 or http://dx.doi.org/10.2139/ssrn.3117881

Zhuanxin Ding (Contact Author)

Analytic Investors ( email )

555 West Fifth Street
50th Floor
Los Angeles, CA 90017
United States

R. Douglas Martin

University of Washington ( email )

Applied Mathematics & Statistics
Dept. of Statistics
Seattle, WA 98195
United States

Chaojun Yang

Shanghai Jiao Tong University (SJTU) ( email )

1954 Huashan Rd
Shanghai, 200030
China

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