In this article, we study cascading failures in time-varying and uncertain financial networks. First, we develop a stochastic dynamic model for the mean and covariance matrix of the market value of each company in the network. Second, we provide a steady-state analysis, we characterize equilibrium points, and we provide conditions for the asymptotic stability of such points. For the covariance matrix, the dynamics have the form of a Lyapunov equation and simulating such dynamics can be viewed as a numerical method to compute the steady-state solution. As a general insight, the dynamics reveal the probability of failure of each company during the transient and at steady state. Finally, we perform a robust analysis to obtain bounding sets for the mean market value in the absence of information on the covariance.
Ramirez, S., Hoven, M.v.d., Bauso, D. (2023). A Stochastic Model for Cascading Failures in Financial Networks. IEEE TRANSACTIONS ON CONTROL OF NETWORK SYSTEMS, 10(4), 1950-1961 [10.1109/tcns.2023.3256273].
A Stochastic Model for Cascading Failures in Financial Networks
Bauso, Dario
2023-12-01
Abstract
In this article, we study cascading failures in time-varying and uncertain financial networks. First, we develop a stochastic dynamic model for the mean and covariance matrix of the market value of each company in the network. Second, we provide a steady-state analysis, we characterize equilibrium points, and we provide conditions for the asymptotic stability of such points. For the covariance matrix, the dynamics have the form of a Lyapunov equation and simulating such dynamics can be viewed as a numerical method to compute the steady-state solution. As a general insight, the dynamics reveal the probability of failure of each company during the transient and at steady state. Finally, we perform a robust analysis to obtain bounding sets for the mean market value in the absence of information on the covariance.File | Dimensione | Formato | |
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