News implied volatility and disaster concerns

• 成果类型: Article
• 署名作者: Manela, Asaf; Moreira, Alan
• 署名单位: Washington University (WUSTL); Yale University
• 刊物名称: JOURNAL OF FINANCIAL ECONOMICS
• ISSN/ISSBN: 0304-405X
• DOI: 10.1016/j.jfineco.2016.01.032
• 发表日期: 2017
• 页码: 137-162
• 关键词: Text-based analysis; implied volatility; rare disasters; equity premium; Return predictability; Machine Learning

摘要

We construct a text-based measure of uncertainty starting in 1890 using front-page articles of the Wall Street Journal. News implied volatility (NVIX) peaks during stock market crashes, times of policy-related uncertainty, world wars, and financial crises. In US postwar data, periods when NVIX is high are followed by periods of above average stock returns, even after controlling for contemporaneous and forward-looking measures of stock market volatility. News coverage related to wars and government policy explains most of the time variation in risk premia our measure identifies. Over the longer 1890-2009 sample that includes the Great Depression and two world wars, high NVIX predicts high future returns in normal times and rises just before transitions into economic disasters. The evidence is consistent with recent theories emphasizing time variation in rare disaster risk as a source of aggregate asset prices fluctuations. (C) 2016 Elsevier B.V. All rights reserved.