Mesoscopic approach to minority games in herd regime

TL;DR

This paper introduces a mesoscopic framework for analyzing minority games in the herd regime, simplifying the state space to better understand macroscopic behaviors like demand patterns and predictability.

Contribution

It develops a mesoscale state representation for minority games, enabling explicit probability calculations and analysis of macroscopic properties.

Findings

Reduced state space as a Markov process with computable probabilities

Finiteness of states for any payoff function proved

Explanation of demand variance and predictability patterns

Abstract

We study minority games in efficient regime. By incorporating the utility function and aggregating agents with similar strategies we develop an effective mesoscale notion of state of the game. Using this approach, the game can be represented as a Markov process with substantially reduced number of states with explicitly computable probabilities. For any payoff, the finiteness of the number of states is proved. Interesting features of an extensive random variable, called aggregated demand, viz. its strong inhomogeneity and presence of patterns in time, can be easily interpreted. Using Markov theory and quenched disorder approach, we can explain important macroscopic characteristics of the game: behavior of variance per capita and predictability of the aggregated demand. We prove that in case of linear payoff many attractors in the state space are possible.