The Cyber Risk Premium

Published Online:https://doi.org/10.1287/mnsc.2022.02056

References

  • Amihud Y (2002) Illiquidity and stock returns: Cross-section and time-series effects. J. Financial Markets 5(1):31–56.CrossrefGoogle Scholar
  • Ang A, Hodrick RJ, Xing Y, Zhang X (2006) The cross-section of volatility and expected returns. J. Finance 61(1):259–299.CrossrefGoogle Scholar
  • Binfarè M (2019) The real effects of risk management vulnerabilities: Evidence from data breaches. Preprint, submitted October 21, https://dx.doi.org/10.2139/ssrn.3411553.Google Scholar
  • Brodersen KH, Ong CS, Stephan KE, Buhmann JM (2010) The balanced accuracy and its posterior distribution. Proc. 20th Internat. Conf. Pattern Recognition (IEEE, Piscataway, NJ), 3121–3124.Google Scholar
  • Chen L, Pelger M, Zhu J (2023) Deep learning in asset pricing. Management Sci. 70(2):v-vi, 671–1342, iii-iv.Google Scholar
  • Cong LW, Feng G, He J, He X (2023a) Asset pricing with panel tree under global split criteria. NBER Working Paper No. 30805, National Bureau of Economic Research, Cambridge, MA.Google Scholar
  • Cong LW, Harvey CR, Rabetti D, Wu Z-Y (2023b) An anatomy of crypto-enabled cybercrimes. NBER Working Paper No. 30834, National Bureau of Economic Research, Cambridge, MA.Google Scholar
  • Cong LW, Tang K, Wang J, Zhang Y (2021) Alphaportfolio: Direct construction through deep reinforcement learning and interpretable AI. Preprint, submitted August 1, https://dx.doi.org/10.2139/ssrn.554486.Google Scholar
  • Damashek M (1995) Gauging similarity with n-Grams: Language-independent categorization of text. Science 267(5199):843–848.CrossrefGoogle Scholar
  • Duffie D, Younger J (2019) Cyber runs. Working paper, Hutchins Center on Fiscal and Monetary Policy, Washington, DC.Google Scholar
  • Eisenbach TM, Kovner A, Lee MJ (2020) Cyber risk and the US financial system: A pre-mortem analysis. J. Financial Economics. 145(3):802–826.Google Scholar
  • Fama EF, French KR (1988) Permanent and temporary components of stock prices. J. Political Econom. 96(2):246–273.CrossrefGoogle Scholar
  • Fama EF, French KR (1996) Multifactor explanations of asset pricing anomalies. J. Finance 51(1):55–84.CrossrefGoogle Scholar
  • Fama EF, French KR (1997) Industry costs of equity. J. Financial Econom. 43(2):153–193.CrossrefGoogle Scholar
  • Fama EF, MacBeth JD (1973) Risk, return, and equilibrium: Empirical tests. J. Political Econom. 81(3):607–636.CrossrefGoogle Scholar
  • Florackis C, Louca C, Michaely R, Weber M (2023) Cybersecurity risk. Rev. Financial Stud. 36(1):351–407.CrossrefGoogle Scholar
  • Freyberger J, Neuhierl A, Weber M (2020) Dissecting characteristics nonparametrically. Rev. Financial Stud. 33(5):2326–2377.CrossrefGoogle Scholar
  • Gu S, Kelly B, Xiu D (2020) Empirical asset pricing via machine learning. Rev. Financial Stud. 33(5):2223–2273.CrossrefGoogle Scholar
  • Hastie T, Tibshirani R, Friedman J (2017) The Elements of Statistical Learning (Springer Science+Business Media, New York).Google Scholar
  • He H, Garcia EA (2009) Learning from imbalanced data. IEEE Trans. Knowledge Data Engrg. 21(9):1263–1284.CrossrefGoogle Scholar
  • Hoberg G, Philips GM (2016) Text-based network industries and endogenous product differentiation. J. Political Econom. 124(5):1423–1465.CrossrefGoogle Scholar
  • Jamilov R, Rey H, Tahoun A (2020) The anatomy of cyber risk. NBER Working Paper No. 28906, National Bureau of Economic Research, London Business School, London.Google Scholar
  • Kamiya S, Kang J-K, Kim J, Milidonis A, Stulz RM (2021) Risk management, firm reputation, and the impact of successful cyberattacks on target firms. J. Financial Econom. 139(3):719–749.CrossrefGoogle Scholar
  • Kashyap AK, Wetherilt A (2019) Some principles for regulating cyber risk. AEA Papers Proc. 109:482–487.CrossrefGoogle Scholar
  • Kelly BT, Pruitt S, Su Y (2019) Characteristics are covariances: A unified model of risk and return. J. Financial Econom. 134(3):501–524.CrossrefGoogle Scholar
  • King G, Zeng L (2001) Logistic regression in rare events data. Political Anal. 9(2):137–163.CrossrefGoogle Scholar
  • Kopp E, Kaffenberger L, Jenkinson N (2017) Cyber Risk, Market Failures, and Financial Stability (International Monetary Fund, Washington, DC).CrossrefGoogle Scholar
  • Kozak S, Nagel S, Santosh S (2020) Shrinking the cross-section. J. Financial Econom. 135(2):271–292.CrossrefGoogle Scholar
  • Li K, Mai F, Shen R, Yan X (2021) Measuring corporate culture using machine learning. Rev. Financial Stud. 34(7):3265–3315.CrossrefGoogle Scholar
  • Lin Z, Sapp TR, Ulmer JR, Parsa R (2020) Insider trading ahead of cyber breach announcements. J. Financial Markets 50:100527.CrossrefGoogle Scholar
  • Liu X-Y, Wu J, Zhou Z-H (2008) Exploratory undersampling for class-imbalance learning. IEEE Trans. Systems Man Cybernetics B Cybernetics 39(2):539–550.Google Scholar
  • Michel A, Oded J, Shaked I (2020) Do security breaches matter? The shareholder puzzle. Eur. Financial Management 26(2):288–315.CrossrefGoogle Scholar
  • Newey WK, West KD (1987) A simple, positive semi-definite, heteroskedasticity and autocorrelation consistent covariance matrix. Econometrica 55(3):703–708.CrossrefGoogle Scholar
  • Petersen MA (2009) Estimating standard errors in finance panel data sets: Comparing approaches. Rev. Financial Stud. 22(1):435–480.CrossrefGoogle Scholar
  • Schütze H, Manning CD, Raghavan P (2008) Introduction to Information Retrieval, vol. 39 (Cambridge University Press, Cambridge, UK).Google Scholar
  • Warren P, Kaivanto K, Prince D (2018) Could a cyber attack cause a systemic impact in the financial sector? Bank England Quart. Bull. 58:21–30.Google Scholar
  • Whited TM, Wu G (2006) Financial constraints risk. Rev. Financial Stud. 19(2):531–559.CrossrefGoogle Scholar
  • Yue Y, Finley T, Radlinski F, Joachims T (2007) A support vector method for optimizing average precision. Proc. 30th Annual Internat. ACM SIGIR Conf. Res. Development Inform. Retrieval (ACM, New York), 271–278.Google Scholar
  • Zeng X, Martinez TR (2000) Distribution-balanced stratified cross-validation for accuracy estimation. J. Experiment. Theoretical Artificial Intelligence 12(1):1–12.CrossrefGoogle Scholar
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