Information-Driven Volatility

68 Pages Posted: 14 Nov 2021 Last revised: 30 Sep 2022

See all articles by Hengjie Ai

Hengjie Ai

University of Wisconsin-Madison

Leyla Jianyu Han

Boston University - Questrom School of Business

Lai Xu

Syracuse University

Date Written: August 28, 2022

Abstract

Standard asset pricing models with stochastic volatility predict a robust positive relationship between past realized volatility and future expected returns. Empirical work typically finds this relationship to be negative. We develop an asset pricing model where stock market volatility dynamics are driven by information. We show that under strong generalized risk sensitivity of preferences, information-driven volatility induces a negative correlation between past realized volatility and future expected returns. We provide empirical evidence for the unique implications of the information-driven volatility channel and demonstrate that our model can quantitatively replicate the evidence.

Keywords: Information, Return Volatility, Macroeconomic Announcements, Generalized Risk Sensitivity

JEL Classification: D83, D84, G11, G12, G14

Suggested Citation

Ai, Hengjie and Han, Leyla Jianyu and Xu, Lai, Information-Driven Volatility (August 28, 2022). Available at SSRN: https://ssrn.com/abstract=3961096 or http://dx.doi.org/10.2139/ssrn.3961096

Hengjie Ai

University of Wisconsin-Madison ( email )

975 University Avenue
Madison, WI 53706
United States
6088903881 (Phone)

HOME PAGE: http://www.hengjieai.com

Leyla Jianyu Han (Contact Author)

Boston University - Questrom School of Business ( email )

595 Commonwealth Avenue
Boston, MA MA 02215
United States

HOME PAGE: http://www.leylahan.com/

Lai Xu

Syracuse University ( email )

900 S. Crouse Avenue
Syracuse, NY 13244-2130
United States

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