Vulnerability Analysis of the Financial Network

Aein Khabazian () and Jiming Peng ()
Additional contact information
Aein Khabazian: Department of Industrial Engineering, University of Houston, Houston, Texas 77204
Jiming Peng: Department of Industrial Engineering, University of Houston, Houston, Texas 77204

Management Science, 2019, vol. 65, issue 7, 3302-3321

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.

Keywords: financial network; systemic risk; linear optimization; sensitivity analysis; (in)feasibility analysis; stochastic optimization; probability (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (9)

Downloads: (external link)
https://doi.org/10.1287/mnsc.2018.3106 (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:inm:ormnsc:v:65:y:2019:i:7:p:3302-3321

Access Statistics for this article

More articles in Management Science from INFORMS Contact information at EDIRC.
Bibliographic data for series maintained by Chris Asher ().