The Cyber Risk Premium

48 Pages Posted: 15 Jul 2020 Last revised: 22 Sep 2020

See all articles by Hao Jiang

Hao Jiang

Michigan State University

Naveen Khanna

Michigan State University

Qian Yang

Michigan State University

Date Written: June 28, 2020

Abstract

This paper studies how the stock market perceives and prices cyber risk. To estimate the ex-ante likelihood that a firm will experience a cyber attack, we apply cross-validated logistic LASSO regressions to a set of firm and industry characteristics along with an estimate of a firm’s self-perceived level of cyber risk gauged from its 10K. We find this measure of a firm’s vulnerability to cyber attacks influences both investor portfolio choices and stock prices. In particular, institutional investors tend to sell stocks with high cyber risk and buy those with low cyber risk; this tendency is stronger during periods with higher data breach concerns. We document that firms with higher cyber risk tend to have higher average realized stock returns and higher ex-ante cost of equity.

Keywords: Cyber Risk, Cybersecurity, Risk Premium, Machine Learning, LASSO, Cross-Validation

JEL Classification: G11, G12, G14, G17

Suggested Citation

Jiang, Hao and Khanna, Naveen and Yang, Qian, The Cyber Risk Premium (June 28, 2020). Available at SSRN: https://ssrn.com/abstract=3637142 or http://dx.doi.org/10.2139/ssrn.3637142

Hao Jiang

Michigan State University ( email )

315 Eppley Center
Department of Finance
East Lansing, MI 48824
United States

HOME PAGE: http://sites.google.com/site/haojiangfinance/

Naveen Khanna

Michigan State University ( email )

East Lansing, MI 48824-1121
United States
517-353-1853 (Phone)
517-432-1080 (Fax)

Qian Yang (Contact Author)

Michigan State University ( email )

MI 48823
United States

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