Disentangling the sources of cyber risk premia

Details

Ressource 1Download: Disentangling_the_sources_of_cyber_risk_premia.pdf (2715.28 [Ko])
State: Public
Version: author
License: CC BY 4.0
Serval ID
serval:BIB_D7388C791BC9
Type
Article: article from journal or magazin.
Collection
Publications
Institution
Title
Disentangling the sources of cyber risk premia
Journal
arXiv
Author(s)
Maréchal Loïc, Monnet Nathan
Publication state
Submitted to the publisher
Language
english
Abstract
We use a methodology based on a machine learning algorithm to quantify firms’ cyber risks based on their disclosures and a dedicated cyber corpus. The model can identify paragraphs related to determined cyber-threat types and accordingly attribute several related cyber scores to the firm. The cyber scores are unrelated to other firms’ characteristics. Stocks with high cyber scores significantly outperform other stocks. The long-short cyber risk factors have positive risk premia, are robust to all factors’ benchmarks, and help price returns. Furthermore, we suggest the market does not distinguish between different types of cyber risks but instead views them as a single, aggregate cyber risk.
Open Access
Yes
Create date
22/01/2025 15:03
Last modification date
23/01/2025 7:20
Usage data