Predictive regressions

• 成果类型: Article
• 署名作者: Stambaugh, RF
• 署名单位: University of Pennsylvania; National Bureau of Economic Research
• 刊物名称: JOURNAL OF FINANCIAL ECONOMICS
• ISSN/ISSBN: 0304-405X
• DOI: 10.1016/S0304-405X(99)00041-0
• 发表日期: 1999
• 页码: 375-421
• 关键词: regression; BIAS; Bayesian analysis; Estimation risk; asset allocation; PREDICTING RETURNS

摘要

When a rate of return is regressed on a lagged stochastic regressor, such as a dividend yield, the regression disturbance is correlated with the regressor's innovation. The OLS estimator's finite-sample properties, derived here, can depart substantially from the standard regression setting. Bayesian posterior distributions for the regression parameters are obtained under specifications that differ with respect to (i) prior beliefs about the autocorrelation of the regressor and (ii) whether the initial observation of the regressor is specified as fixed or stochastic. The posteriors differ across such specifications, and asset allocations in the presence of estimation risk exhibit sensitivity to those differences. (C) 1999 Elsevier Science S.A. All rights reserved. JEL classification. C32; C11; G11.