Agentic Empirical Asset Pricing: Methodological Foundations

The paper introduces Agentic Empirical Asset Pricing (AEAP), a framework where autonomous LLM agents conduct the entire scientific discovery process for asset pricing. It outlines AEAP’s core components, critiques current evaluation methods that only test outputs, and proposes a new reference architecture with rigorous standards for factor discovery and out‑of‑sample backtesting. Using this framework, the authors evaluate SEADS against five baselines on US equity panels, finding no single metric consistently ranks the systems and highlighting the need for multi‑axis evaluation and rolling re‑execution to assess reliability of the discovery process.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv AI.

• llms
• agents