Agentic Trading: When LLM Agents Meet Financial Markets

Excerpt

arXiv:2605.19337v2 Announce Type: replace Abstract: Large Language Models (LLMs) combined with autonomous agent architectures are shifting quantitative finance from isolated predictive modeling toward closed-loop trading agents. These systems perceive multimodal market signals, maintain context and memory, reason about decisions, emit executable trading actions, and adapt to non-stationary market regimes. This survey provides a systematic synthesis of agentic trading through an Architecture--Cap