Evolutionary analysis and computing of the financial safety net

Abstract

Governments want to establish a financial safety net (FSN) to prevent financial crises from spreading. The FSN is a series of institutional arrangements to preserve financial stability. In the real FSN, it includes the central bank, deposit insurance institutions and their premium, commercial banks and their benefit rates, etc., and these parameters are interdependent and dynamic change. And thus, analysis and computing of the FSN is very challenging. Inspired by evolutionary game theory, in this paper, we first establish a network game model of the FSN to analyze the evolution of bank deposit insurance strategies, and further propose a method to measure the effectiveness of the FSN. Finally, we use computational experiments to simulate the operation of the FSN. In the experiments, an evolutionary computation method is employed to compute banks’ decisions to reduce computing time. Experimental results show that our evolutionary approach is suitable for the FSN, and is able to provide suggestions of macro policy for regulators.