DeepAI AI Chat
Log In Sign Up

Reinforcement Learning Policy Recommendation for Interbank Network Stability

by   Alessio Brini, et al.

In this paper we analyze the effect of a policy recommendation on the performances of an artificial interbank market. Financial institutions stipulate lending agreements following a public recommendation and their individual information. The former, modeled by a reinforcement learning optimal policy trying to maximize the long term fitness of the system, gathers information on the economic environment and directs economic actors to create credit relationships based on the optimal choice between a low interest rate or high liquidity supply. The latter, based on the agents' balance sheet, allows to determine the liquidity supply and interest rate that the banks optimally offer on the market. Based on the combination between the public and the private signal, financial institutions create or cut their credit connections over time via a preferential attachment evolving procedure able to generate a dynamic network. Our results show that the emergence of a core-periphery interbank network, combined with a certain level of homogeneity on the size of lenders and borrowers, are essential features to ensure the resilience of the system. Moreover, the reinforcement learning optimal policy recommendation plays a crucial role in mitigating systemic risk with respect to alternative policy instruments.


page 1

page 2

page 3

page 4


Revisiting Exploration-Conscious Reinforcement Learning

The objective of Reinforcement Learning is to learn an optimal policy by...

A Learning and Control Perspective for Microfinance

Microfinance in developing areas such as Africa has been proven to impro...

Comparative Analysis of Economic Instruments in Intersection Operation: A User-Based Perspective

Focusing on different economic instruments implemented in intersection o...

Would Friedman Burn your Tokens?

Cryptocurrencies come with a variety of tokenomic policies as well as as...

From Persistent Homology to Reinforcement Learning with Applications for Retail Banking

The retail banking services are one of the pillars of the modern economi...

Evaluation of Deep Reinforcement Learning Algorithms for Portfolio Optimisation

We evaluate benchmark deep reinforcement learning (DRL) algorithms on th...