Researchers replaced human subjects with LLM agents in double auction market experiments and found that LLM-populated markets converge more slowly to equilibrium than human markets, resulting in less efficient resource allocation. Analysis revealed significant heterogeneity in trading behavior across model families and roles, with agents shifting from strategic reasoning to urgency when deciding to trade.