Return Predictability, Economic Profits, and Model Mis-Specification: How Important are the Better Specified Models?

摘要：

This paper addresses the question whether investors can profit from return predictability in the real world while focusing on the impact of the data-generating process (DGP). We estimate an array of predictive models ranging from the simplest VAR to nonparametric ones and evaluate their out-of-sample portfolio performance with various predictive variables. We find that despite the significant statistical improvement the better specified predictive models do not consistently outperform the VAR. Another striking finding is that investors appear to be better off predicting only the sign but not the magnitude of the market expected excess returns.

关键词： return predictability economic value model mis-specification data-generating process VAR GARCH seminonparametric model Model selection criteria recursive estimation out of sample portfolio performance no-short-sale switching strategy market t

作者: Yufeng Han

作者单位: A.B.Freeman School of Business, Tulane University, 7 McAlister Drive, New Orleans, LA 70118

会议类型: 国际会议

会议名称: 2007年中国金融国际年会

会议地点: 成都

会议语种:英文

页码: 1-49

在线出版日期: 2007-07-09（万方平台首次上网日期，不代表论文的发表时间）