Spherical grand-canonical minority games with and without score discounting

TL;DR

This paper introduces a spherical grand-canonical minority game model, providing analytical solutions for its phases and transitions, including effects of score discounting and agent heterogeneity, advancing understanding of complex adaptive systems.

Contribution

It develops a solvable spherical version of the GCMG that incorporates score discounting, enabling analytical phase analysis and revealing conditions for efficiency with heterogeneous memory loss.

Findings

Analytical phase diagrams for the spherical GCMG.

Efficiency depends on agent heterogeneity and memory loss.

Exact volatility expressions in ergodic phases.

Abstract

We present a spherical version of the grand-canonical minority game (GCMG), and solve its dynamics in the stationary state. The model displays several types of transitions between multiple ergodic phases and one non-ergodic phase. We derive analytical solutions, including exact expressions for the volatility, throughout all ergodic phases, and compute the phase behaviour of the system. In contrast to conventional GCMGs, where the introduction of memory-loss precludes analytical approaches, the spherical model can be solved also when exponential discounting is taken into account. For the case of homogeneous incentives to trade epsilon and memory loss rates rho, an efficient phase is found only if rho=epsilon=0. Allowing for heterogeneous memory-loss rates we find that efficiency can be achieved as long as there is any finite fraction of agents which is not subject to memory loss.