The Self Driving Portfolio: Agentic Architecture for Institutional Asset Management

Abstract: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.

Artificial Intelligence (cs.AI); Multiagent Systems (cs.MA); General Finance (q-fin.GN); Portfolio Management (q-fin.PM)

I.2.1; I.2.6; I.2.7; I.2.11; J.4; H.4.2

arXiv:2604.02279 [cs.AI]

(or arXiv:2604.02279v2 [cs.AI] for this version)

https://doi.org/10.48550/arXiv.2604.02279 Focus to learn more arXiv-issued DOI via DataCite

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