A Market Model Explores Why Bounded Rationality Can Persist

A preprint by Cheng Zhang uses evolutionary game theory to examine how different trading behaviors might persist in financial markets, even when they perform differently.

What the study found

Zhang models a market with two types of behavior: relatively rational trading and boundedly rational trading. Their shares change under replicator dynamics, a framework in which a behavior’s relative performance affects how its share evolves. Performance depends on the prevalence of the other type and on trading frictions.

According to the preprint, when the types interact complementarily and their friction difference is moderate, the model has a unique, globally asymptotically stable mix of both. In this scenario, rational traders profit from mispricing associated with boundedly rational traders, while the latter benefit from liquidity and price correction supplied by rational traders. When the interaction is antagonistic, the corresponding mixed point instead acts as a tipping threshold between two regimes, each containing one type.

Why it matters

The model offers a theoretical explanation for why boundedly rational behavior need not disappear simply because rational traders compete with it. Zhang also reports that reducing the costs of disciplined trading shifts the modeled mix toward rational trading, but eliminates bounded rationality only if the cost advantage exceeds a threshold. The abstract associates lower costs with algorithmic and AI-based trading; the result is a model prediction, not evidence of a measured market effect.

Limits and unknowns

This is an arXiv preprint based on a theoretical model, not an empirical demonstration that the proposed mechanism operates in real markets. The abstract does not provide the model’s equations, the threshold’s value, empirical tests or details of how its assumptions map onto particular markets.

Read the research

Authors: Cheng Zhang

Published: 2026-10-29

Source basis: Based on the abstract only

Original abstract

Classical theory predicts that irrational traders lose money to rational traders and are eventually driven out of the market. Yet noise trading, herding, and heuristic trading persist even in highly developed markets. We model a financial market as an ecology of two trading-behavior types, relatively rational (R) and boundedly rational (N), whose composition evolves under replicator dynamics according to relative performance. Each type's fitness depends on the share of the other type and on frictions. When the interaction is complementary, that is, rational traders profit from the mispricing created by boundedly rational traders while the latter benefit from the liquidity and price correction supplied by the former, and when the difference in frictions is moderate, a unique interior composition exists and is globally asymptotically stable: bounded rationality persists endogenously. When the interaction is antagonistic, the same point becomes a tipping threshold between two one-type regimes. Comparative statics show that lowering the costs of disciplined trading, as algorithmic and AI-based trading does, shifts the composition toward rational trading continuously but does not eliminate bounded rationality unless the cost advantage exceeds an explicit threshold.

This article is an AI-generated adaptation, not a substitute for the original research. Preprints may not have been peer reviewed; AI can make mistakes.