Can LLMs simulate human aversion in bond market trading?
Shifting Power: Leveraging LLMs to Simulate Human Aversion in ABMs of Bilateral Financial Exchanges, A bond market study
This paper introduces TRIBE, a multi-agent model simulating a bilateral bond market where agents (market makers) interact with clients to trade bonds. It explores how adding human-like trade aversion, simulated via LLMs, impacts market dynamics.
Key LLM findings include: even slightly mentioning "aversion" in LLM prompts leads to complete trade cessation; giving clients LLM-powered "timeliness" decisions (whether to trade right now) drastically reduces trading activity, shifts power to clients, and destabilizes the market due to the unpredictability of client behavior. This highlights the significant impact of LLM-driven agent behavior, especially when simulating human-like nuances in multi-agent systems.