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Computing the probability of a financial market failure: a new measure of systemic risk

Author

Listed:
  • Robert Jarrow

    (Cornell University)

  • Philip Protter

    (Columbia University)

  • Alejandra Quintos

    (University of Wisconsin-Madison)

Abstract

This paper characterizes the probability of a market failure defined as the default of two or more globally systemically important banks (G-SIBs) in a small interval of time. The default probabilities of the G-SIBs are correlated through the possible existence of a market-wide stress event. The characterization employs a multivariate Cox process across the G-SIBs, which allows us to relate our work to the existing literature on intensity-based models. Various theorems related to market failure probabilities are derived, including the probability of a market failure due to two banks defaulting over the next infinitesimal interval, the probability of a catastrophic market failure, the impact of increasing the number of G-SIBs in an economy, and the impact of changing the initial conditions of the economy’s state variables. We also show that if there are too many G-SIBs, a market failure is inevitable, i.e., the probability of a market failure tends to 1.

Suggested Citation

  • Robert Jarrow & Philip Protter & Alejandra Quintos, 2024. "Computing the probability of a financial market failure: a new measure of systemic risk," Annals of Operations Research, Springer, vol. 336(1), pages 481-503, May.
    • Handle: RePEc:spr:annopr:v:336:y:2024:i:1:d:10.1007_s10479-022-05146-9
    DOI: 10.1007/s10479-022-05146-9
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