Asymmetric impact of earnings news on investor uncertainty

Zihang Peng, David Johnstone and Demetris Christodoulou

Journal of Business Finance & Accounting, 2020, vol. 47, issue 1-2, 3-26

Abstract: We describe a model that predicts an asymmetric impact of disclosure on investor uncertainty. We show that good news tends to resolve more uncertainty than bad news, and that uncertainty can be revised upwards if the investors' prior belief is sufficiently strong and the signal is sufficiently bad. This result is in contrast to classical disclosure models, where new information always resolves uncertainty and the change in uncertainty depends only on the relative precision of the news. Using option‐implied volatility as a proxy for uncertainty, we find strong support for our predictions. We also show that our results are robust to competing explanations, notably to the leverage effect and volatility feedback, as well as to the jump risk induced in anticipation of the earnings announcements.

Date: 2020
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