FactorEngine mines alpha factors as Turing-complete code via LLM-guided directional search, parameter separation, and a multi-agent pipeline that converts financial reports into executable programs, delivering higher IC/ICIR and Sharpe ratios than baselines in backtests.
Navigating the alpha jungle: An llm-powered mcts framework for formulaic factor mining
3 Pith papers cite this work. Polarity classification is still indexing.
verdicts
UNVERDICTED 3representative citing papers
CogAlpha combines LLM reasoning with code-level evolutionary search to discover financial alphas that show higher predictive accuracy and generalization than prior methods on five stock datasets.
AlphaSAGE is a GFlowNet framework with an RGCN structure-aware encoder and dense multi-faceted rewards that mines diverse, novel, and predictive formulaic alphas for quantitative trading.
citing papers explorer
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FactorEngine: A Program-level Knowledge-Infused Factor Mining Framework for Quantitative Investment
FactorEngine mines alpha factors as Turing-complete code via LLM-guided directional search, parameter separation, and a multi-agent pipeline that converts financial reports into executable programs, delivering higher IC/ICIR and Sharpe ratios than baselines in backtests.
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Cognitive Alpha Mining via LLM-Driven Code-Based Evolution
CogAlpha combines LLM reasoning with code-level evolutionary search to discover financial alphas that show higher predictive accuracy and generalization than prior methods on five stock datasets.
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AlphaSAGE: Structure-Aware Alpha Mining via GFlowNets for Robust Exploration
AlphaSAGE is a GFlowNet framework with an RGCN structure-aware encoder and dense multi-faceted rewards that mines diverse, novel, and predictive formulaic alphas for quantitative trading.