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Vulnerability Analysis of the Financial Network

Author

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  • Aein Khabazian

    (Department of Industrial Engineering, University of Houston, Houston, Texas 77204)

  • Jiming Peng

    (Department of Industrial Engineering, University of Houston, Houston, Texas 77204)

Abstract

Since the financial crisis in 2007–2008, the vulnerability of a financial system has become a major concern in financial engineering. In this paper, we analyze the vulnerability of a financial network based on the linear optimization model introduced by Eisenberg and Noe [Eisenberg L, Noe TH (2001) Systemic risk in financial systems. Management Sci . 47(2):236–249.], in which the right-hand side of the constraints is subject to market shock and only limited information regarding the liability matrix is exposed. We develop a new extended sensitivity analysis to characterize the conditions under which a bank is solvent, in default, or bankrupted and estimate the probability of insolvency and the probability of bankruptcy under mild conditions on the market shock and the network structure. Particularly, we show that although an increment in the total asset may not be able to improve the stability of the financial system, a larger asset inequality in the system will reduce its stability. Moreover, under a certain assumption on the market shock and the network structure, we show that the least stable network can be attained at some network with a monopoly node, which also has the highest probability of insolvency. The probability of bankruptcy in the network when all the nodes receive shocks is estimated. We also estimate the impact of bankruptcy of the monopoly node in a well-balanced network and explore the domino effect of bankruptcy when the network has a tridiagonal structure. Numerical experiments are presented to verify the theoretical conclusions.

Suggested Citation

  • Aein Khabazian & Jiming Peng, 2019. "Vulnerability Analysis of the Financial Network," Management Science, INFORMS, vol. 65(7), pages 3302-3321, July.
    • Handle: RePEc:inm:ormnsc:v:65:y:2019:i:7:p:3302-3321
    DOI: 10.1287/mnsc.2018.3106
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    References listed on IDEAS

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    2. Chao, Xiangrui & Ran, Qin & Chen, Jia & Li, Tie & Qian, Qian & Ergu, Daji, 2022. "Regulatory technology (Reg-Tech) in financial stability supervision: Taxonomy, key methods, applications and future directions," International Review of Financial Analysis, Elsevier, vol. 80(C).
    3. Ahmadian, Navid & Lim, Gino J. & Cho, Jaeyoung & Bora, Selim, 2020. "A quantitative approach for assessment and improvement of network resilience," Reliability Engineering and System Safety, Elsevier, vol. 200(C).
    4. Maria Rosa Borges & Lauriano Ulica & Mariya Gubareva, 2020. "Systemic risk in the Angolan interbank payment system – a network approach," Applied Economics, Taylor & Francis Journals, vol. 52(45), pages 4900-4912, September.
    5. Shane Barratt & Stephen Boyd, 2020. "Multi-Period Liability Clearing via Convex Optimal Control," Papers 2005.09066, arXiv.org.
    6. Hezhi Luo & Xiaodong Ding & Jiming Peng & Rujun Jiang & Duan Li, 2021. "Complexity Results and Effective Algorithms for Worst-Case Linear Optimization Under Uncertainties," INFORMS Journal on Computing, INFORMS, vol. 33(1), pages 180-197, January.
    7. Xiong, Shi & Chen, Weidong, 2022. "A robust hybrid method using dynamic network analysis and Weighted Mahalanobis distance for modeling systemic risk in the international energy market," Energy Economics, Elsevier, vol. 109(C).

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