TiMi：将交易策略设计与分钟级部署分离

文章 arXiv papers · 作者: Zifan Song et al.

总结

本文介绍 TiMi，这是一种用于量化交易的多智能体系统，将交易策略开发与分钟级执行分开。该系统为语言模型分配专业任务，例如解读市场信息、编写交易机器人和进行数学推理。其流程从整体市场模式开始，再定制策略，随后通过反馈循环改进并部署最终策略。

论文报告称，该系统在超过200个股票和加密货币交易对上进行了评估，并声称其在波动市场中盈利稳定、操作高效且能控制风险。摘要未提供表现数据、比较方法，也未说明数据选择、交易成本或样本外测试的细节。这些缺失使人难以判断结果有多稳健，也难以评估系统能否迁移到实盘交易。

核心观点

TiMi 将策略开发与分钟级部署分开。
该系统为语言模型分配语义分析、编程和数学推理等角色。
其分析流程从整体市场模式推进到定制策略。
系统使用数学反馈循环来改进交易策略。
论文报告称，系统在股票和加密货币交易对上进行了评估，但对评估设计提供的信息有限。

Recent advancements in large language models (LLMs) and agentic systems have shown exceptional decision-making capabilities, revealing significant potential for autonomic finance. Current financial trading agents predominantly simulate anthropomorphic roles that inadvertently introduce emotional biases and rely on peripheral information, while being constrained by the necessity for continuous inference during deployment. In this paper, we pioneer the harmonization of strategic depth in agents with the mechanical rationality essential for quantitative trading. Consequently, we present TiMi (Trade in Minutes), a rationality-driven multi-agent system that architecturally decouples strategy development from minute-level deployment. TiMi leverages specialized LLM capabilities of semantic analysis, code programming, and mathematical reasoning within a comprehensive policy-optimization-deployment chain. Specifically, we propose a two-tier analytical paradigm from macro patterns to micro customization, layered programming design for trading bot implementation, and closed-loop optimization driven by mathematical reflection. Extensive evaluations across 200+ trading pairs in stock and cryptocurrency markets empirically validate the efficacy of TiMi in stable profitability, action efficiency, and risk control under volatile market dynamics.

在遵守原作品许可的前提下，附作者信息全文展示。许可协议: abstract CC0

此摘要由 Stratmill 研究智能体根据原文撰写，并非原文副本。

TiMi：将交易策略设计与分钟级部署分离

总结

核心观点

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