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What the hack: Systematic risk contagion from cyber events

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  • Corbet, Shaen
  • Gurdgiev, Constantin

Abstract

This paper examines the impact of cybercrime and hacking events on equity market volatility across publicly traded corporations. The volatility influence of these cybercrime events is shown to be dependent on the number of clients exposed across all sectors and the type of the cyber security breach event, with significantly large volatility effects presented for companies who find themselves exposed to cybercrime in the form of hacking. Evidence is presented to suggest that corporations with large data breaches are punished substantially in the form of stock market volatility and significantly reduced abnormal stock returns. Companies with lower levels of market capitalisation are found to be most susceptible. In an environment where corporate data protection should be paramount, minor breaches appear to be relatively unpunished by the stock market. We also show that there is a growing importance in the contagion channel from cybersecurity breaches to markets volatility. Systematic weakness in the existent mechanisms for cybersecurity oversight and enforcement could be improved through the ring-fenced incentivisation of both current and ex-hackers. Their expertise is central to the identification of weak corporate cybersecurity practices.

Suggested Citation

  • Corbet, Shaen & Gurdgiev, Constantin, 2019. "What the hack: Systematic risk contagion from cyber events," International Review of Financial Analysis, Elsevier, vol. 65(C).
  • Handle: RePEc:eee:finana:v:65:y:2019:i:c:s1057521919300274
    DOI: 10.1016/j.irfa.2019.101386
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    1. Anat Hovav & John D'Arcy, 2003. "The Impact of Denial‐of‐Service Attack Announcements on the Market Value of Firms," Risk Management and Insurance Review, American Risk and Insurance Association, vol. 6(2), pages 97-121, September.
    2. Nelson, Daniel B, 1991. "Conditional Heteroskedasticity in Asset Returns: A New Approach," Econometrica, Econometric Society, vol. 59(2), pages 347-370, March.
    3. Robert Engle, 2004. "Risk and Volatility: Econometric Models and Financial Practice," American Economic Review, American Economic Association, vol. 94(3), pages 405-420, June.
    4. Kraemer-Mbula, Erika & Tang, Puay & Rush, Howard, 2013. "The cybercrime ecosystem: Online innovation in the shadows?," Technological Forecasting and Social Change, Elsevier, vol. 80(3), pages 541-555.
    5. Baillie, Richard T & Bollerslev, Tim, 2002. "The Message in Daily Exchange Rates: A Conditional-Variance Tale," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(1), pages 60-68, January.
    6. Acemoglu, Daron & Malekian, Azarakhsh & Ozdaglar, Asu, 2016. "Network security and contagion," Journal of Economic Theory, Elsevier, vol. 166(C), pages 536-585.
    7. Bastiaan Overvest & Bas Straathof, 2015. "What drives cybercrime? Empirical evidence from DDoS attacks," CPB Discussion Paper 306.rdf, CPB Netherlands Bureau for Economic Policy Analysis.
    8. Bastiaan Overvest & Bas Straathof, 2015. "What drives cybercrime? Empirical evidence from DDoS attacks," CPB Discussion Paper 306, CPB Netherlands Bureau for Economic Policy Analysis.
    9. Camerer, Colin & Loewenstein, George & Weber, Martin, 1989. "The Curse of Knowledge in Economic Settings: An Experimental Analysis," Journal of Political Economy, University of Chicago Press, vol. 97(5), pages 1232-1254, October.
    10. Geoffrey Heal & Howard Kunreuther, 2004. "Interdependent Security: A General Model," NBER Working Papers 10706, National Bureau of Economic Research, Inc.
    11. Geoffrey Heal & Howard Kunreuther, 2007. "Modeling Interdependent Risks," Risk Analysis, John Wiley & Sons, vol. 27(3), pages 621-634, June.
    12. Ciner, Cetin & Gurdgiev, Constantin & Lucey, Brian M., 2013. "Hedges and safe havens: An examination of stocks, bonds, gold, oil and exchange rates," International Review of Financial Analysis, Elsevier, vol. 29(C), pages 202-211.
    13. Dungey, Mardi & Gajurel, Dinesh, 2015. "Contagion and banking crisis – International evidence for 2007–2009," Journal of Banking & Finance, Elsevier, vol. 60(C), pages 271-283.
    14. Kevin M. Gatzlaff & Kathleen A. McCullough, 2010. "The Effect of Data Breaches on Shareholder Wealth," Risk Management and Insurance Review, American Risk and Insurance Association, vol. 13(1), pages 61-83, March.
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    Cited by:

    1. Gunay, Samet & Goodell, John W. & Muhammed, Shahnawaz & Kirimhan, Destan, 2023. "Frequency connectedness between FinTech, NFT and DeFi: Considering linkages to investor sentiment," International Review of Financial Analysis, Elsevier, vol. 90(C).
    2. Mazaher Kianpour & Stewart J. Kowalski & Harald Øverby, 2021. "Systematically Understanding Cybersecurity Economics: A Survey," Sustainability, MDPI, vol. 13(24), pages 1-28, December.
    3. Goodell, John W. & Corbet, Shaen, 2023. "Commodity market exposure to energy-firm distress: Evidence from the Colonial Pipeline ransomware attack," Finance Research Letters, Elsevier, vol. 51(C).
    4. Akyildirim, Erdinc & Corbet, Shaen & O'Connell, John F. & Sensoy, Ahmet, 2021. "The influence of aviation disasters on engine manufacturers: An analysis of financial and reputational contagion risks," International Review of Financial Analysis, Elsevier, vol. 74(C).
    5. Corbet, Shaen & Goodell, John W., 2022. "The reputational contagion effects of ransomware attacks," Finance Research Letters, Elsevier, vol. 47(PB).
    6. Nadine Gatzert & Madeline Schubert, 2022. "Cyber risk management in the US banking and insurance industry: A textual and empirical analysis of determinants and value," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 89(3), pages 725-763, September.
    7. Tosun, Onur Kemal, 2021. "Cyber-attacks and stock market activity," International Review of Financial Analysis, Elsevier, vol. 76(C).
    8. Daniel Castillo & Joseph Falzon, 2018. "An Analysis of the Impact of WannaCry Cyberattack on Cybersecurity Stock Returns," Review of Economics & Finance, Better Advances Press, Canada, vol. 13, pages 93-100, August.

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    More about this item

    Keywords

    EGARCH; Financial markets; Cybercrime; Regulation;
    All these keywords.

    JEL classification:

    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets
    • G32 - Financial Economics - - Corporate Finance and Governance - - - Financing Policy; Financial Risk and Risk Management; Capital and Ownership Structure; Value of Firms; Goodwill
    • G38 - Financial Economics - - Corporate Finance and Governance - - - Government Policy and Regulation

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