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

Robert Jarrow (), Philip Protter () and Alejandra Quintos ()
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Philip Protter: Columbia University
Alejandra Quintos: University of Wisconsin-Madison

Annals of Operations Research, 2024, vol. 336, issue 1, No 15, 503 pages

Abstract: 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.

Keywords: Systemic risk; Market failure probabilities; G-SIBs; Multivariate Cox processes (search for similar items in EconPapers)
Date: 2024
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Working Paper: Computing the Probability of a Financial Market Failure: A New Measure of Systemic Risk (2022)
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DOI: 10.1007/s10479-022-05146-9

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