arXiv AI By Haochen Luo, Yifan Li, Binh Minh An, Xiaolong Luo, Zhengzhao Lai, Yuan Zhang, Chen Liu

LiveOption: Evaluating LLM Agents in Structured Option Trading with Nonlinear Payoffs

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LiveOption is an evaluation framework designed to assess large language model (LLM) agents in option trading, a domain characterized by nonlinear payoffs and multi-leg strategy construction. The framework treats option trading as structured sequential decision-making under realistic execution and capital constraints, offering a reproducible environment with standardized interaction protocols. It includes three task suites—portfolio overlays, event-driven earnings trading, and 0DTE intraday trading—and introduces a hierarchical metric suite that evaluates action validity, decision quality, risk characteristics, and outcome-level performance, revealing that current agents often fail to achieve competitive returns.

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arXiv AI
Jun 9

Beyond Agent Architecture: Execution Assumptions and Reproducibility in LLM-Based Trading Systems

arXiv:2606. 08285v1 Announce Type: new Abstract: Large language models (LLMs) and agentic systems are increasingly proposed for financial trading, yet their reported performance remains difficult to compare because studies vary in data provenance, temporal split discipline, execution timing, turnover treatment, and transaction-cost modeling.

By Junyi Yao, Zihao Zheng