Deciding Bank Interest Rates -- A Major-Minor Impulse Control Mean-Field Game Perspective

Fuente: arXiv
Saved in:
Bibliographic Details
Main Authors: Chen, Fan, Martin, Nicholas, Chen, Po-Yu, Wang, Xiaozhen, Ren, Zhenjie, Buet-Golfouse, Francois
Format: Preprint
Published: 2024
Subjects:
Online Access:
Tags: Add Tag
No Tags, Be the first to tag this record!
_version_ 1866912175888531456
author Chen, Fan
Martin, Nicholas
Chen, Po-Yu
Wang, Xiaozhen
Ren, Zhenjie
Buet-Golfouse, Francois
author_facet Chen, Fan
Martin, Nicholas
Chen, Po-Yu
Wang, Xiaozhen
Ren, Zhenjie
Buet-Golfouse, Francois
contents Deciding bank interest rates has been a long-standing challenge in finance. It is crucial to ensure that the selected rates balance market share and profitability. However, traditional approaches typically focus on the interest rate changes of individual banks, often neglecting the interactions with other banks in the market. This work proposes a novel framework that models the interest rate problem as a major-minor mean field game within the context of an interbank game. To incorporate the complex interactions between banks, we utilize mean-field theory and employ impulsive control to model the overhead in rate adjustments. Ultimately, we solve this optimal control problem using a new deep Q-network method, which iterates the parameterized action value functions for major and minor players and updates the networks in a Fictitious Play way. Our proposed algorithm converges, offering a solution that enables the analysis of strategies for major and minor players in the market under the Nash Equilibrium.
format Preprint
id arxiv_https___arxiv_org_abs_2411_14481
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Deciding Bank Interest Rates -- A Major-Minor Impulse Control Mean-Field Game Perspective
Chen, Fan
Martin, Nicholas
Chen, Po-Yu
Wang, Xiaozhen
Ren, Zhenjie
Buet-Golfouse, Francois
Optimization and Control
Probability
Deciding bank interest rates has been a long-standing challenge in finance. It is crucial to ensure that the selected rates balance market share and profitability. However, traditional approaches typically focus on the interest rate changes of individual banks, often neglecting the interactions with other banks in the market. This work proposes a novel framework that models the interest rate problem as a major-minor mean field game within the context of an interbank game. To incorporate the complex interactions between banks, we utilize mean-field theory and employ impulsive control to model the overhead in rate adjustments. Ultimately, we solve this optimal control problem using a new deep Q-network method, which iterates the parameterized action value functions for major and minor players and updates the networks in a Fictitious Play way. Our proposed algorithm converges, offering a solution that enables the analysis of strategies for major and minor players in the market under the Nash Equilibrium.
title Deciding Bank Interest Rates -- A Major-Minor Impulse Control Mean-Field Game Perspective
topic Optimization and Control
Probability
url https://arxiv.org/abs/2411.14481