mlsanityData to 7 Oct 2026

The Self Driving Portfolio: Agentic Architecture for Institutional Asset Management

arXiv 2604.02279 ↗First posted 2 Apr 2026cs.AI cs.MA q-fin.GNcited by 0

On the map: LLM agents and tool use → Financial trading and forecasting agents

Abstract (arXiv)

Agentic AI shifts the investor's role from analytical execution to oversight. We present an agentic strategic asset allocation pipeline in which 44 specialized agents produce capital market assumptions, construct portfolios using 21 competing methods, and critique and vote on each other's outputs. 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.

Key facts. No citing papers in the map yet (data through 7 Oct 2026). Placed in Financial trading and forecasting agents, one of 16 directions in LLM agents and tool use. Builds on 10 of its 56 references that are in the map. First posted on arXiv 2 Apr 2026.

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10 of 56 references.

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  1. 2024FinCon: A Synthesized LLM Multi-Agent System with Conceptual Verbal Reinforcement for Enhanced Financial Decision Making9 Jul

Other references · 9

  1. 2023Judging LLM-as-a-Judge with MT-Bench and Chatbot Arenacited by 8,393
  2. 2023A Survey on Large Language Model based Autonomous Agentscited by 2,203
  3. 2023AutoGen: Enabling Next-Gen LLM Applications via Multi-Agent Conversationcited by 1,906
  4. 2023MetaGPT: Meta Programming for A Multi-Agent Collaborative Frameworkcited by 1,761
  5. 2024A Multimodal Foundation Agent for Financial Trading: Tool-Augmented, Diversified, and Generalistcited by 137
  6. 2024LLM Voting: Human Choices and AI Collective Decision Makingcited by 47
  7. 2025Levels of Autonomy for AI Agentscited by 45
  8. 2026DatedGPT: Preventing Lookahead Bias in Large Language Models with Time-Aware Pretrainingcited by 7
  9. 2026Defensible Design for OpenClaw: Securing Autonomous Tool-Invoking Agentscited by 4

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