用50个智能代理自动构建和优化投资组合，像人一样决策并自我改进。
The Self Driving Portfolio: Agentic Architecture for Institutional Asset Management
- 50个专业智能体分工协作，从市场预测到组合构建全流程自治
- 通过相互评审投票选出最优方案，提升策略可靠性
- 可自学习调整，适合机构投资者部署自动化投资系统
代理式人工智能将投资者角色从执行转向监督。我们提出一个代理式战略资产配置流程，包含约50个专业化智能体，负责生成资本市场假设、使用20多种竞争性方法构建投资组合，并相互评审与投票。研究者代理会提出尚未被涵盖的新组合构建方法，元代理则对比历史预测与实际回报，改写代理代码与提示以优化未来表现。整个流程由《投资政策声明》（Investment Policy Statement）统一管控，该文件原本用于指导人类投资经理，如今也可约束和引导自主智能体。
原文摘要 · Abstract (English)
Agentic AI shifts the investor's role from analytical execution to oversight. We present an agentic strategic asset allocation pipeline in which approximately 50 specialized agents produce capital market assumptions, construct portfolios using over 20 competing methods, and critique and vote on each other's output. A researcher agent proposes new portfolio construction methods not yet represented, and a meta-agent compares past forecasts against realized returns and rewrites agent code and prompts to improve future performance. The entire pipeline is governed by the Investment Policy Statement--the same document that guides human portfolio managers can now constrain and direct autonomous agents.
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