TESTING THE PREDICTIVE POWER OF DIVIDEND YIELDS

• 成果类型: Note
• 署名作者: GOETZMANN, WN; JORION, P
• 署名单位: University of California System; University of California Irvine
• 刊物名称: JOURNAL OF FINANCE
• ISSN/ISSBN: 0022-1082
• DOI: 10.2307/2328917
• 发表日期: 1993
• 页码: 663-679
• 关键词: consistent covariance-matrix; heteroskedasticity; estimators

摘要

This paper reexamines the ability of dividend yields to predict long-horizon stock returns. We use the bootstrap methodology, as well as simulations, to examine the distribution of test statistics under the null hypothesis of no forecasting ability. These experiments are constructed so as to maintain the dynamics of regressions with lagged dependent variables over long horizons. We find that the empirically observed statistics are well within the 95% bounds of their simulated distributions. Overall there is no strong statistical evidence indicating that dividend yields can be used to forecast stock returns.