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.
Mathematical discoveries from program search with large language models
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LLM framework combines network topology and domain knowledge for iterative DSM sequencing optimization and outperforms stochastic and deterministic baselines on convergence speed and solution quality.
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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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Large Language Models for Combinatorial Optimization of Design Structure Matrix
LLM framework combines network topology and domain knowledge for iterative DSM sequencing optimization and outperforms stochastic and deterministic baselines on convergence speed and solution quality.