Business School Doctoral Symposium: Information Intensity and Earnings Announcement Risk Pricing Jingjing Chen | Events | Calendar | News

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December 12, 2022 (Monday)

11:00 am to noon


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Information Strength and Pricing of Earnings Announcement Risk


Earnings announcements pose obvious risks for investors. We speculate that, in frictional markets, the premium for earnings announcement risk may be realized in a discrete process and concentrated during periods of high cash flow news intensity. When there are updates on cash flow news and changes in cash flow uncertainty, investors adjust their expectations for stock returns and factor the premium into the stock price. We construct an ex-ante measure of expected information intensity (EII) based on expected corporate events and find a significant positive relationship between earnings announcement risk and stock returns when firms have high EII. A viable strategy for long (short) stocks with high (low) earnings announcement risk yields a return of 0.58% per month (6.96% annualized) in Fama-French five-factor alpha. Furthermore, we show that, consistent with our conjecture, premiums are primarily earned around company announcement dates. We provide additional evidence that information production and consumption trigger risk pricing.

Dr Ait Chen

Dr. Chen Jingjing

Jingjing Chen is a visiting assistant professor at Northeastern University. She has a Ph.D. BA in Finance from Washington State University. Her research interests are empirical asset pricing, sustainable investing, market microstructure and derivatives. Jingjing’s research examines how information feeds into asset prices, and what drives asset returns in the short term (liquidity, attention) and long term (cash flow, regulation, ESG preferences). She has an article published in the Journal of Banking and Finance and several working papers.

Jingjing teaches undergraduate, graduate and MBA courses.Her teaching interests include investing, corporate finance, financial modeling, quantitative portfolio management, fintech, quantitative

Financial and data analysis. In 2021, Jingjing won the Outstanding Doctoral Student Teaching Award.


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