The Cyber Risk Premium

• 成果类型: Article
• 署名作者: Jiang, Hao; Khanna, Naveen; Yang, Qian; Zhou, Jiayu
• 署名单位: Michigan State University; Michigan State University's Broad College of Business; McMaster University; Michigan State University
• 刊物名称: MANAGEMENT SCIENCE
• ISSN/ISSBN: 0025-1909
• DOI: 10.1287/mnsc.2022.02056
• 发表日期: 2024
• 关键词: Cyber risk; Cybersecurity; Risk premium; Machine Learning

摘要

Cyber risk is an important emerging source of risk in the economy. To estimate its impact on the asset market, we use machine learning techniques to develop a firm-level measure of cyber risk. The measure aggregates information from a rich set of firm characteristics and shows superior ability to forecast future cyberattacks on individual firms. We find that firms with higher cyber risk earn higher average stock returns. When these firms underperform, cybersecurity experts tend to have higher concerns about cyber risk, and cybersecurity exchange-traded funds outperform. Further tests strengthen the identification of the cyber risk premium.