OpenFinArena/FinDeepForecast
Financial Deep Forecasting (FinDeepForecast) The current paradigm for evaluating Large Language Models (LLMs) and AI Agents in financial analysis is constrained by its reliance on static, historical datasets. This approach primarily assesses a model's capacity to interpret past events rather than forecast future outcomes. This methodological misalignment with real-world practice fails to simulate the dynamic, looking-forward environments that analysts and economists face. To… See the full description on the dataset page: https://huggingface.co/datasets/OpenFinArena/FinDeepForecast.
| Author / organization | OpenFinArena |
|---|---|
| License (as declared) | apache-2.0 |
| Downloads | 162 (as reported by Hugging Face) |
| Likes | 0 |
| Created | 28 October 2025 |
| Last updated at source | 16 January 2026 |
Recent changes
- 16 Oct 2026 Description: Financial Deep Forecasting (FinDeepForecast) The current paradigm for evaluating Large Language Models (LLMs) and AI Agents in financial analysis is constrained by its reliance on static, historical datasets. This approach primarily assesse → Financial Deep Forecasting (FinDeepForecast) The current paradigm for evaluating Large Language Models (LLMs) and AI Agents in financial analysis is constrained by its reliance on static, historical datasets. This approach primarily assesse
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Silytics shows public metadata from Hugging Face and links to the original. Information may be incomplete or out of date. Last refreshed 16 October 2026. Licenses and terms of the original apply to the work itself. Not financial, legal or professional advice.