Predicting anomaly performance with politics, the weather, global warming, sunspots, and the stars

• 成果类型: Article
• 署名作者: Novy-Marx, Robert
• 署名单位: University of Rochester
• 刊物名称: JOURNAL OF FINANCIAL ECONOMICS
• ISSN/ISSBN: 0304-405X
• DOI: 10.1016/j.jfineco.2014.02.002
• 发表日期: 2014
• 页码: 137-146
• 关键词: PREDICTIVE REGRESSIONS; Anomaly performance

摘要

Predictive regressions find that the party of the US president, the weather in Manhattan, global warming, the El Nino phenomenon, sunspots, and the conjunctions of the planets all have significant power predicting the performance of popular anomalies. The interpretation of these results has important implications for the asset pricing literature. (C) 2014 Elsevier B.V. All rights reserved.