The Cyber Risk Premium

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