LLMs Write and Evolve Code to Redefine Quantitative Factor Mining – The CogAlpha ACL Paper

The CogAlpha framework upgrades Alpha discovery from static formulas to executable Python code, organizes a 7‑layer, 21‑agent research hierarchy, iteratively evolves factor candidates, and on CSI300 10‑day prediction outperforms 21 baselines with a 16.39% annual excess return and an IR of 1.8999, demonstrating that large models can actively participate in the discovery process.

ACL 2026Alpha MiningEvolutionary Algorithms

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LLMs Write and Evolve Code to Redefine Quantitative Factor Mining – The CogAlpha ACL Paper

Bighead's Algorithm Notes

Aug 31, 2025 · Artificial Intelligence

Paper Review: AlphaEval – A Comprehensive, Efficient Framework for Evaluating Alpha Mining

AlphaEval is a unified, parallelizable evaluation framework that assesses Alpha mining models across predictive ability, time stability, market‑perturbation robustness, financial logic, and diversity without backtesting, matching full backtest results while offering higher efficiency and open‑source reproducibility.

Alpha MiningEvaluation FrameworkLLM

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Paper Review: AlphaEval – A Comprehensive, Efficient Framework for Evaluating Alpha Mining

Bighead's Algorithm Notes

Aug 28, 2025 · Artificial Intelligence

Key AI-Driven Quantitative Finance Papers from KDD2025

This article summarizes recent AI research on quantitative finance, covering AlphaAgent's LLM-driven alpha mining, UMI's multi‑level irrationality factors, PDU's progressive dependency learning for stock ranking, SSPT's stock‑specific pretraining transformer, and Enhancer's distribution‑aware meta‑learning framework, all of which demonstrate improved stock prediction and resistance to alpha decay.

Alpha MiningFinancial AILLM

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Key AI-Driven Quantitative Finance Papers from KDD2025