Volatility and Agent Adaptability in a Self-Organizing Market

TL;DR

This paper investigates how adaptive agents in a self-organizing market influence volatility, revealing that increased adaptability can minimize market fluctuations in a bar-attendance model.

Contribution

It introduces a model of adaptive agents with random prediction rules and analyzes how their adaptability affects market volatility.

Findings

Volatility can be minimized through increased agent adaptability.

Mean attendance remains close to the bar's cut-off value.

Agent prediction rules are randomly assigned from a pool.

Abstract

We present results for the so-called `bar-attendance' model of market behavior: $p$ adaptive agents, each possessing $n$ prediction rules chosen randomly from a pool, attempt to attend a bar whose cut-off is $s$. The global attendance time-series has a mean near, but not equal to, $s$. The variance, or `volatility', can show a minimum with increasing adaptability of the individual agents.