报告题目：Assessment and Mitigation of Systemic Risk in Financial System under Uncertainties
报告人：Jiming Peng (University of Houston)
报告校内联系人： 张立卫 教授 联系电话: 0411-84708351-8118
Abstract: Since the financial crisis in 2007-2008, the assessment and control of systemic risk in a financial network has become a major concern in finance and economics. In this talk, we study the vulnerability of a financial network based on the linear optimization model introduced by Eisenberg and Noe (2001), where the right hand side of the constraints is subject to market shock and only partial information regarding the liability matrix is revealed. We develop a new extended sensitivity analysis to characterize the conditions under which a bank is solvent, 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 while an increment in the social asset may not able to improve the stability of the financial system, a larger asset inequality in the system will reduce its stability. Moreover, under certain assumption on the market shock and the network structure, we show that the least stable network can be attained at some monopoly network, 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 study the vulnerability of a well-balanced ring network and explore the domino effect of bankruptcy in it. Numerical experiments are presented to verify the theoretical conclusions.
If time allows, we will also discuss how to assess the systemic risk under uncertain liabilities via identifying the worst- and best-case scenarios of the liability matrix for fixed assets. Numerical experiments demonstrate that the contagious risk in the worst-case scenario is much more significant than what has been underestimated in the current literature. We also use the identified best-case scenario to develop a strategy for systemic risk mitigation. We evaluate the performance of the new strategy on a multi-period risk mitigation problem in which both the asset vector and the liability matrix are assumed to be uncertain. Numerical experiment shows that compared with other strategies in the literature, the proposed strategy reaches the minimal bailout cost under a full bailout policy.
Biography: Jiming Peng is an associate professor in the department of industrial engineering, University of Houston. Prior to this, he had worked in McMaster University in Canada and University of Illinois at Urbana-Champaign. His recent research interest lies mainly in optimization modeling, theoretical analysis and algorithm design with applications to healthcare, big data and finance. He has published a research monograph by Princeton University Press and over sixty papers in major optimization journals and various CS/IEEE conference proceedings. His research has been recognized by numerous awards from academic communities and supported by various funding agencies in Canada and USA.