# Selection mechanisms affect volatility in evolving markets

## TL;DR

This paper investigates how different evolutionary selection mechanisms in markets influence macro-level volatility, highlighting the impact of local fitness-proportionate selection on market risk and volatility correlations.

## Contribution

It introduces a simulation framework with evolving zero-intelligence agents and compares the effects of different selection mechanisms on market volatility and risk correlations.

## Key findings

- Local fitness-proportionate selection correlates with macro-volatility.
- Quantile-based selection shows less correlation with volatility.
- Selection mechanisms significantly influence market macro-statistics.

## Abstract

Financial asset markets are sociotechnical systems whose constituent agents are subject to evolutionary pressure as unprofitable agents exit the marketplace and more profitable agents continue to trade assets. Using a population of evolving zero-intelligence agents and a frequent batch auction price-discovery mechanism as substrate, we analyze the role played by evolutionary selection mechanisms in determining macro-observable market statistics. In particular, we show that selection mechanisms incorporating a local fitness-proportionate component are associated with high correlation between a micro, risk-aversion parameter and a commonly-used macro-volatility statistic, while a purely quantile-based selection mechanism shows significantly less correlation.