On Testing Time Series Momentum Using Predictive Regressions

39 Pages Posted: 7 Nov 2020

See all articles by Lei Jiang

Lei Jiang

Tsinghua University

Liang Peng

Georgia State University - Risk Management & Insurance Department

Zhongling Qin

Auburn University - Department of Finance

Bingduo Yang

Sun Yat-Sen Univeristy

Date Written: September 8, 2020

Abstract

In studies of time series momentum (TSM), the Newey-West t-test has size distortion for linear predictive regression with excess returns because of non-stationarity, endogeneity due to correlated errors, and a lack of finite moments due to heavy tails. To solve these problems, we propose a new test that features log-returns, a model of the error correlations, and weighted least squares estimation. Simulations confirm the proper size and increased power of the new test. Empirically, we find weak support for TSM regardless of the predictor's time horizon and a different set of assets with TSM compared with using the Newey-West t-test.

Keywords: Time Series Momentum, Log-returns, Return Predictability, Predictive Regression

JEL Classification: G11; G23; C58

Suggested Citation

Jiang, Lei and Peng, Liang and Qin, Zhongling and Yang, Bingduo, On Testing Time Series Momentum Using Predictive Regressions (September 8, 2020). Available at SSRN: https://ssrn.com/abstract=3678727 or http://dx.doi.org/10.2139/ssrn.3678727

Lei Jiang (Contact Author)

Tsinghua University ( email )

Beijing, 100084
China

Liang Peng

Georgia State University - Risk Management & Insurance Department

P.O. Box 4036
Atlanta, GA 30302-4036
United States

Zhongling Qin

Auburn University - Department of Finance ( email )

Harbert College of Business
Auburn, AL 36849
United States

Bingduo Yang

Sun Yat-Sen Univeristy ( email )

Xingang Rd Wst. 135
Guangzhou, Guangdong 510275
China

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