QuantAgents: Towards Multi-agent Financial System via Simulated Trading
- URL: http://arxiv.org/abs/2510.04643v1
- Date: Mon, 06 Oct 2025 09:45:57 GMT
- Title: QuantAgents: Towards Multi-agent Financial System via Simulated Trading
- Authors: Xiangyu Li, Yawen Zeng, Xiaofen Xing, Jin Xu, Xiangmin Xu,
- Abstract summary: QuantAgents is a multi-agent system integrating simulated trading.<n> QuantAgents comprises four agents: a simulated trading analyst, a risk control analyst, a market news analyst, and a manager.<n>Our system incentivizes agents to receive feedback on two fronts: performance in real-world markets and predictive accuracy in simulated trading.
- Score: 40.636918662488505
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: In this paper, our objective is to develop a multi-agent financial system that incorporates simulated trading, a technique extensively utilized by financial professionals. While current LLM-based agent models demonstrate competitive performance, they still exhibit significant deviations from real-world fund companies. A critical distinction lies in the agents' reliance on ``post-reflection'', particularly in response to adverse outcomes, but lack a distinctly human capability: long-term prediction of future trends. Therefore, we introduce QuantAgents, a multi-agent system integrating simulated trading, to comprehensively evaluate various investment strategies and market scenarios without assuming actual risks. Specifically, QuantAgents comprises four agents: a simulated trading analyst, a risk control analyst, a market news analyst, and a manager, who collaborate through several meetings. Moreover, our system incentivizes agents to receive feedback on two fronts: performance in real-world markets and predictive accuracy in simulated trading. Extensive experiments demonstrate that our framework excels across all metrics, yielding an overall return of nearly 300% over the three years (https://quantagents.github.io/).
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