Long-horizon regressions: theoretical results and applications

• 成果类型: Article
• 署名作者: Valkanov, R
• 署名单位: University of California System; University of California Los Angeles
• 刊物名称: JOURNAL OF FINANCIAL ECONOMICS
• ISSN/ISSBN: 0304-405X
• DOI: 10.1016/S0304-405X(03)00065-5
• 发表日期: 2003
• 页码: 201-232
• 关键词: PREDICTIVE REGRESSIONS; long-horizon predictions; stock returns; Fisher effect

摘要

I use asymptotic arguments to show that the t-statistics in long-horizon regressions do not converge to well-defined distributions. In some cases, moreover, the ordinary least squares estimator is not consistent and the R 2 is an inadequate measure of the goodness of fit. These findings can partially explain the tendency, of long-horizon regressions to find significant results where previous short-term approaches find none. I propose a rescaled t-statistic, whose asymptotic distribution is easy to simulate, and revisit some of the long-horizon evidence on return predictability and of the Fisher effect. (C) 2003 Elsevier Science B.V. All rights reserved.