Hubble is an LLM-driven framework that safely discovers diverse alpha factors via operator trees, RAG feedback, and out-of-sample validation on US equity data, with range and volatility factors showing persistence.
Alphaagent: Llm-driven alpha mining with regularized exploration to counteract alpha decay
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An LLM-driven evolutionary framework that writes and evolves Python-coded trading factors reports large gains in predictive accuracy on CSI300, but with incomplete validation.
Reproducibility audit of 30 LLM trading papers shows execution assumptions under-reported relative to agent architectures, illustrated by a 10-equity example where frictions compress returns.
citing papers explorer
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Hubble: An LLM-Driven Agentic Framework for Safe, Diverse, and Reproducible Alpha Factor Discovery
Hubble is an LLM-driven framework that safely discovers diverse alpha factors via operator trees, RAG feedback, and out-of-sample validation on US equity data, with range and volatility factors showing persistence.
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Cognitive Alpha Mining via LLM-Driven Code-Based Evolution
An LLM-driven evolutionary framework that writes and evolves Python-coded trading factors reports large gains in predictive accuracy on CSI300, but with incomplete validation.
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Beyond Agent Architecture: Execution Assumptions and Reproducibility in LLM-Based Trading Systems
Reproducibility audit of 30 LLM trading papers shows execution assumptions under-reported relative to agent architectures, illustrated by a 10-equity example where frictions compress returns.