5月7日 | Liang Peng:On Testing Time Series Momentum Using Predictive Regressions

时间:2021-04-26浏览:194设置

时  间:2021年5月7日(周五) 9:00-10:00

地  点:腾讯会议ID:148 674 809

题  目:On Testing Time Series Momentum Using Predictive Regressions

主讲人:Liang Peng Professor ,Georgia State University

主持人:钱林义

摘  要:

In studies of time series momentum (TSM), the classical and Newey-West $t$-tests have size distortions 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 its accurate size and increased power. Empirically, for futures contracts, we find weaker support for TSM at short horizons and, notably, stronger support at long horizons. For speculatively owned stock portfolios, we find overstated TSM.

报告人简介:

Dr. Peng has been the Thomas P Bowles chair professor of actuarial science in the department of Risk Management and Insurance in the Robinson College of Business at Georgia State University since August 2014. He was a faculty in the School of Mathematics at Georgia Institute of Technology from January 2001 to August 2014. He was promoted to associate professor with tenure in 2006 and to full professor in 2009. Dr. Peng has been the RMI Ph.D. program coordinator from January 2018 to December 2020. Dr. Peng has published one book on heavy tailed data analysis and 160 papers in various journals in statistics, econometrics, and actuarial science. 

 


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