AI Agents 相关度: 9/10

The Self Driving Portfolio: Agentic Architecture for Institutional Asset Management

Andrew Ang, Nazym Azimbayev, Andrey Kim
arXiv: 2604.02279v1 发布: 2026-04-02 更新: 2026-04-02

AI 摘要

该论文提出了一种基于Agentic AI的自动化资产管理框架,旨在提升投资效率和决策质量。

主要贡献

  • 提出了Agentic资产配置流程
  • 引入元Agent进行自我改进
  • 使用投资政策声明约束Agent行为

方法论

构建包含多个专业Agent的pipeline,Agent之间协作、竞争和评估,元Agent持续优化,受IPS约束。

原文摘要

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.

标签

Agentic AI Asset Management Portfolio Optimization Financial AI Automation

arXiv 分类

cs.AI cs.MA q-fin.GN q-fin.PM