LLMs can be profile-calibrated to exhibit human-like behavioral parameters including loss aversion, herding, and extrapolation, enabling agent-based models to generate momentum and reversal patterns consistent with empirical asset pricing evidence.
Returns to buying winners and selling losers: Implications for stock market efficiency.Journal of Finance, 48(1):65–91
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Calibrating Behavioral Parameters with Large Language Models
LLMs can be profile-calibrated to exhibit human-like behavioral parameters including loss aversion, herding, and extrapolation, enabling agent-based models to generate momentum and reversal patterns consistent with empirical asset pricing evidence.