Large Banks and Systemic Risk: Insights from a Mean-Field Game Model

28 May 2023  ·  Yuanyuan Chang, Dena Firoozi, David Benatia ·

This paper presents a dynamic game framework to analyze the role of large banks in the interbank market. By extending existing models, we incorporate a major bank as a dynamic decision-maker interacting with multiple small banks. Using the mean field game methodology and convex analysis, best-response trading strategies are derived, leading to an approximate equilibrium for the interbank market. We investigate the influence of the large bank on the market stability by examining individual default probabilities and systemic risk, through the use of Monte Carlo simulations. Our findings reveal that, when the size of the major bank is not excessively large, it can positively contribute to market stability. However, there is also the potential for negative spillover effects in the event of default, leading to an increase in systemic risk. The magnitude of this impact is further influenced by the size and trading rate of the major bank. Overall, this study provides valuable insights into the management of systemic risk in the interbank market.

PDF Abstract
No code implementations yet. Submit your code now

Datasets


  Add Datasets introduced or used in this paper

Results from the Paper


  Submit results from this paper to get state-of-the-art GitHub badges and help the community compare results to other papers.

Methods