Abstract
Using a representative agent model in which the investor is averse to ambiguity (Knightian uncertainty) and sees an ambiguous piece of news about the fundamental value of a risky asset, I show a number of predictions for the dynamics of stocks around news: Stocks respond more strongly to bad news than to good news, respond positively to neutral news, and increase on average through news. In times of high ambiguity, the magnitudes of each eect is larger, and the volatility of stocks around news changes in a predictable manner as well. I provide empirical evidence consistent with the model by analyzing the high-frequency behavior of the aggregate stock market around macroeconomic news announcements from November, 1997 to March, 2014. The model helps to understand features of the data that challenge existing frameworks; e.g., the ndings that the stock market reacts especially strongly to bad news versus good
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
