Markets with Heterogeneous Agents: Dynamics and Survival of Bayesian vs. No-Regret Learners

ArXi:2502.08597v3 Announce Type: replace-cross We analyze the performance of heterogeneous learning agents in asset markets with stochastic payoffs. Our main focus is on comparing Bayesian learners and no-regret learners who compete in markets and identifying the conditions under which each approach is effective. We formally relate the notions of survival and market dominance studied in economics and the framework of regret minimization, thereby bridging these theories.