Paper Detail

The Self Driving Portfolio: Agentic Architecture for Institutional Asset Management

Andrew Ang, Nazym Azimbayev, Andrey Kim

arxiv Score 4.8

Published 2026-04-02 · First seen 2026-04-04

General AI

Abstract

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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BibTeX

@article{ang2026self,
  title = {The Self Driving Portfolio: Agentic Architecture for Institutional Asset Management},
  author = {Andrew Ang and Nazym Azimbayev and Andrey Kim},
  year = {2026},
  abstract = {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 promp},
  url = {https://arxiv.org/abs/2604.02279},
  keywords = {cs.AI, cs.MA, q-fin.GN, q-fin.PM},
  eprint = {2604.02279},
  archiveprefix = {arXiv},
}

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