Option Pricing of Earnings Announcement Risks

• 成果类型: Article
• 署名作者: Dubinsky, Andrew; Johannes, Michael; Kaeck, Andreas; Seeger, Norman J.
• 署名单位: Columbia University; University of Sussex; Vrije Universiteit Amsterdam
• 刊物名称: REVIEW OF FINANCIAL STUDIES
• ISSN/ISSBN: 0893-9454
• DOI: 10.1093/rfs/hhy060
• 发表日期: 2019
• 页码: 646
• 关键词: stock-prices; political uncertainty; stochastic volatility; information-content; MARKET UNCERTAINTY; cross-section; Ex-ante; IMPACT; premia; jump

摘要

This paper uses option prices to learn about the equity price uncertainty surrounding information released on earnings announcement dates. To do this, we introduce reduced-form models and estimators to separate price uncertainty about earnings announcements from normal day-to-day volatility. Empirically, we find strong support for the importance of earnings announcements. We find that the anticipated price uncertainty is quantitatively large, varies across time, and is informative about the future return volatility. Finally, we quantify the impact of earnings announcements on formal option pricing models.