OpenFinGym: A Verifiable Multi-Task Gym Environment for Evaluating Quant Agents
arXiv:2606.26350v1 Announce Type: new Abstract: Although large language model agents are increasingly applied to quantitative-finance workflows, their evaluation remains fragmented across isolated tasks, while the financial relevance of benchmark tasks is often overlooked. Yet financial workflows are inherently multi-stage, spanning interdependent tasks such as forecasting, strategy construction, risk management, and trading. Existing platforms typically focus on a single task, and can therefore
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Computer Science > Artificial Intelligence arXiv:2606.26350 (cs) [Submitted on 24 Jun 2026] Title:OpenFinGym: A Verifiable Multi-Task Gym Environment for Evaluating Quant Agents Authors:Kaicheng Zhang, Wen Ge, Lei Jiang, Weixin Yang, Jordan Langham-Lopez, Jialin Yu, Lukasz Szpruch, Hao Ni View a PDF of the paper titled OpenFinGym: A Verifiable Multi-Task Gym Environment for Evaluating Quant Agents, by Kaicheng Zhang and 7 other authors View PDF HTML (experimental) Abstract:Although large language model agents are increasingly applied to quantitative-finance workflows, their evaluation remains fragmented across isolated tasks, while the financial relevance of benchmark tasks is often overlooked.
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