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LLM agents that turn plain language into trading strategies
What it is
LLM-powered trading agents that turn natural language descriptions into strategies built on five pillars: trend, mean reversion, momentum, volume and risk. Each strategy is hosted, configurable and designed to evolve over time. Developers and researchers who want to describe trading ideas in plain words and iterate on them quickly are the intended users. Strategies generated this way still need careful testing, since language model output can misread the intended rules.
At a glance
Research onlyOur rating, based on popularity, maintenance and how ready it is for real use.
| Best for | Developers |
|---|---|
| Used for | Strategy research, AI agents |
| Markets | Multi-market |
| Stack | Python |
| Learning curve | Moderate learning curve |
| Practical value | Medium practical value |
| Cost | Free, with paid APIs |
| Hardware | No GPU needed |
| Maintenance | Last commit 7 days ago |
GitHub stars, last 30 days
Daily snapshots since 2026-09-28 (up to 30 days): +3 over the period, now 390. Gaps mean no snapshot was taken that day.
LLM-powered trading agents that turn plain natural language into a five-pillar strategy: Trend, Mean-Reversion, Momentum, Volume, and Risk. Each strategy is hosted, self-evolving, configurable through
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