OpenFinGym: A Verifiable Multi-Task Gym Environment for Evaluating Quant Agents
- URL: http://arxiv.org/abs/2606.26350v1
- Date: Wed, 24 Jun 2026 19:42:55 GMT
- Title: OpenFinGym: A Verifiable Multi-Task Gym Environment for Evaluating Quant Agents
- Abstract summary: We introduce OpenFinGym, a unified gym environment for quantitative-finance agent development.<n>It covers forecasting, market generation, real-time trading, and fraud detection under a single execution and verification interface.<n>OpenFinGym additionally provides an automated task-construction pipeline that turns quantitative finance publications into executable task packages.
- Score: 11.33449680384001
- License: http://creativecommons.org/licenses/by/4.0/
- 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 overstate agent competence and fail to reveal weaknesses in generalization, real-market interaction, and financially meaningful decision-making. We introduce OpenFinGym, a unified gym environment for quantitative-finance agent development that covers forecasting, market generation, real-time trading, and fraud detection under a single execution and verification interface. OpenFinGym additionally provides an automated task-construction pipeline that turns quantitative finance publications into executable task packages; a containerised runtime with a host-side verifier service that supports scalable agent rollouts and prevents runtime train-test leakage; a paper trading engine with a low-latency data-stream design; deferred-resolution support for long-horizon and event-market forecasts; and integration for SFT and RL post-training
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