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Disentangling the sources of cyber risk premia

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  • Loic Mar'echal
  • Nathan Monnet

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.

Suggested Citation

  • Loic Mar'echal & Nathan Monnet, 2024. "Disentangling the sources of cyber risk premia," Papers 2409.08728, arXiv.org.
    • Handle: RePEc:arx:papers:2409.08728
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    References listed on IDEAS

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    1. Fama, Eugene F & French, Kenneth R, 1992. "The Cross-Section of Expected Stock Returns," Journal of Finance, American Finance Association, vol. 47(2), pages 427-465, June.
    2. Rustam Jamilov & Hélène Rey & Ahmed Tahoun, 2021. "The Anatomy of Cyber Risk," NBER Working Papers 28906, National Bureau of Economic Research, Inc.
    3. Chris Florackis & Christodoulos Louca & Roni Michaely & Michael Weber & Itay Goldstein, 2023. "Cybersecurity Risk," The Review of Financial Studies, Society for Financial Studies, vol. 36(1), pages 351-407.
    4. Fama, Eugene F. & French, Kenneth R., 2015. "A five-factor asset pricing model," Journal of Financial Economics, Elsevier, vol. 116(1), pages 1-22.
    5. Arslan-Ayaydin, Özgür & Boudt, Kris & Thewissen, James, 2016. "Managers set the tone: Equity incentives and the tone of earnings press releases," Journal of Banking & Finance, Elsevier, vol. 72(S), pages 132-147.
    6. Gibbons, Michael R & Ross, Stephen A & Shanken, Jay, 1989. "A Test of the Efficiency of a Given Portfolio," Econometrica, Econometric Society, vol. 57(5), pages 1121-1152, September.
    7. repec:bla:jfinan:v:59:y:2004:i:3:p:1259-1294 is not listed on IDEAS
    8. Carhart, Mark M, 1997. "On Persistence in Mutual Fund Performance," Journal of Finance, American Finance Association, vol. 52(1), pages 57-82, March.
    9. Calomiris, Charles W. & Mamaysky, Harry, 2019. "How news and its context drive risk and returns around the world," Journal of Financial Economics, Elsevier, vol. 133(2), pages 299-336.
    10. Diego García, 2013. "Sentiment during Recessions," Journal of Finance, American Finance Association, vol. 68(3), pages 1267-1300, June.
    11. Francisco Barillas & Jay Shanken, 2018. "Comparing Asset Pricing Models," Journal of Finance, American Finance Association, vol. 73(2), pages 715-754, April.
    12. Fama, Eugene F & MacBeth, James D, 1973. "Risk, Return, and Equilibrium: Empirical Tests," Journal of Political Economy, University of Chicago Press, vol. 81(3), pages 607-636, May-June.
    13. Bodnaruk, Andriy & Loughran, Tim & McDonald, Bill, 2015. "Using 10-K Text to Gauge Financial Constraints," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 50(4), pages 623-646, August.
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