  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.
