ENDOGENEITY AND MOMENTS IN TIME SERIES MOMENTUM'S PREDICTABILITY TEST

• 成果类型: Article
• 署名作者: Jiang, Lei; Peng, Liang; Qin, Hongling; Yang, Bingduo
• 署名单位: University System of Ohio; Kent State University; Kent State University Salem; Kent State University Kent; University System of Georgia; Georgia State University; Auburn University System; Auburn University; Guangdong University of Finance & Economics
• 刊物名称: ANNALS OF APPLIED STATISTICS
• ISSN/ISSBN: 1932-6157
• DOI: 10.1214/24-AOAS1983
• 发表日期: 2025
• 页码: 701-719
• 关键词: likelihood estimators; inference; tail

摘要

The predictability test is critical in developing momentum trading strategies. In time-series momentum (TSM) tests via linear predictive regressions, the classical and Newey-West t-tests have size distortions because of endogeneity and a lack of enough finite moments. To tackle these issues, this paper proposes a new test that features a model of the error correlations, weighted least squares estimation, and the random weighted bootstrap method. Simulations confirm its accurate size and good power. Empirically, we revisit the evidence in (J. Financ. Econ. 135 (2020) 774-794) and find that the TSM predictability detected by the new test is much more widespread than that by the Newey-West t-tests.