OpenPM: Auditable Point-in-Time Evaluation for LLM Portfolio-Management Agents
Large language models are increasingly used to read markets, assess risk, and allocate capital. However, reported results for LLM trading agents can be inflated by look-ahead leakage, optimistic execution, and risk mandates that are described but not enforced. We present OpenPM, an auditable point-in-time evaluation framework for LLM portfolio-management agents. In OpenPM, an agent manages a \$1M long-only book over the S\&P 500 universe using market data at five-minute intervals. Every record visible to the agent must be available at the decision time. Natural-language risk mandates are converted into typed constraints and enforced on the executed portfolio. Each run produces audit artif...
| Authors | Xinying Cai, Minghao Guo, Jiahe Liu et al. |
|---|---|
| Primary category | cs.CE |
| Published | 6 August 2026 |
| Last updated at source | 6 August 2026 |
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