An Iterative Approach to Reduce Systemic Risk among Financial Institutes*. Issue 1 (July 2017)

• Record Type: Journal Article
• Authors: Ye, Xiang-Shen; Xue, Ruo-Bing; Gao, Jian-Jun; Cao, Xi-Ren
• Is Part Of: IFAC-PapersOnLine. Volume 50:Issue 1(2017)
• Page Start: 9380
• Page End: 9385
• Publication Date: 2017-07
• Subjects: Direct-comparison based optimization -- discrete event systems -- financial network -- Markov decision problems -- risk contagion -- policy iteration; Automatic control -- Periodicals; 629.805
• DOI: 10.1016/j.ifacol.2017.08.1447
• Languages: English
• ISSNs: 2405-8963

Abstract

Abstract: Financial institutions are interconnected by holding debt claims against each other. The interconnection is a key contributing factor to the past worldwide financial crisis. A default bank may cause its creditors to default, and the risk may be further propagated to up-stream institutes. We study how the mechanism of default liquidation affects the total wealth of the financial system and curbs the risk contagion. We formulate this problem as a nonlinear optimization problem with equilibrium constraints and propose an optimal liquidation policy to minimize the system's loss without changing the partition of default and non-default banks. We show that the optimization problem resembles a Markov decision problem (MDP) and therefore we can apply the direct-comparison based optimization approach to solve this problem. We derive an iteration algorithm which combines both the policy iteration and the gradient based approach. Our work provides a new direction in curbing the risk contagion in financial networks; and it illustrates the advantages of the direct-comparison based approach, which originated in the field of discrete event dynamic system, in nonlinear optimization problems.