# EvolveTrade: Experience-Driven Policy Refinement for Self-Evolving LLM Trading Agents

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> Полный текст доступен на английском

**Published:** 17 сентября 2026 г.
**Author:** Sehee Kim, Yumin Choi, Minki Kang, Sung Ju Hwang
**Source:** arXiv — cs.AI
**Language:** en-US
**HTML:** https://aiqazaqstan.com/ru/articles/evolvetrade-experience-driven-policy-refinement-for-self-evolving-llm-tr

Large language model (LLM) trading agents can combine market data, news, and executable analysis, but their behavior is often controlled by static hand-written tool-use policies that are fixed before deployment. This limits their ability to adapt how they gather evidence, invoke…

> Материал агрегирован из первоисточника: **arXiv — cs.AI**
> [Читать полностью в arXiv — cs.AI](https://arxiv.org/abs/2609.17632)

**Теги:** #arXiv

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