THE JOURNAL OF FINANCIAL ECONOMICS· VOL.123, ISSUE.1 · JANUARY 2017

新闻的隐含波动率和对灾难的忧虑

作者：Asaf Manela (Washington University), Alan Moreira (Yale University)

摘要：我们使用华尔街日报1890年至今的头版文章，构建了一个从文本上测度不确定性的度量指标。新闻的隐含波动率（NVIX）在股市崩盘时期、政策不确定时期、世界大战时期和金融危机时期达到峰值。根据美国战后时期的数据，在度过了高隐含波动率（NVIX）的严冬后，迎接人们的是股票回报率高于平均水平的时期，即使控制了同期的和预测性的股市波动率之后也依然显著。欧洲杯网站_欧洲杯下注平台-官网推荐战争和政策的新闻报道能够解释该指标中风险溢价中的大部分时间变化性。1890年—2009年的样本区间包括了大萧条时期和两次世界大战时期，显示出高隐含波动率能够预测未来正常时期的高回报率和预测经济灾难的到来。本文的论证与近期的理论一致，该理论强调罕见灾难风险的时间变化性是资产价格波动的加总。

关键字：文本分析，隐含波动率，罕见灾难，股权溢价，收益的可预测性，机器学习

News Implied Volatility and Disaster Concerns

Asaf Manela (Washington University), Alan Moreira (Yale University)

ABSTRACT

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.

Keywords: Text-based analysis, Implied volatility, Rare disasters, Equity premium, Return predictability, Machine learning

原文链接：

http://www.sciencedirect.com/science/article/pii/S0304405X16301751

翻译：吴雨玲