Measuring Risk Information

• 成果类型: Article
• 署名作者: Smith, Kevin C.; So, Eric C.
• 署名单位: Stanford University; Massachusetts Institute of Technology (MIT)
• 刊物名称: JOURNAL OF ACCOUNTING RESEARCH
• ISSN/ISSBN: 0021-8456
• DOI: 10.1111/1475-679X.12413
• 发表日期: 2022
• 页码: 375-426
• 关键词: IMPLIED VOLATILITY; FACTOR DISCLOSURES; earnings; price; uncertainty; cost

摘要

We develop a measure of how information events impact investors' expectations of risk. The measure is broadly applicable and simple to implement. We derive it from an option-pricing model, where investors anticipate an announcement that simultaneously conveys information on the announcer's expected future cash flows and risk profile. We empirically implement the measure using firms' earnings announcements, showing that it closely aligns with our model's predictions and offers strong forecasting power for firms' risk profiles, costs of capital, and future investments. We further highlight pitfalls of using simple changes in option-implied volatilities to study information gleaned from earnings announcements. Finally, we apply our measure to study disclosure regulation, the efficacy of text-based proxies, and market-wide events, which we use to illustrate our measure's uses, and illuminate its potential limitations.