AlphaDiverse is a framework that enhances large language model–based multi‑agent systems for alpha factor mining by addressing cost, availability, and confidentiality constraints. It generates diverse research paths through varied environments and post‑training local agents, then fine‑tunes these agents with supervised learning and optimizes them jointly using a GRPO method that balances predictive quality and diversity. The approach limits research feedback to inner‑period data and evaluates a frozen model on outer‑period data to avoid test‑set tuning, demonstrating competitive prediction and broader exploration across four Chinese stock universes.
By Qingzhuo Wang, Zikun Wei, Zhihua Wei, Wen Shen
AlphaMemo is a self‑evolving alpha‑mining agent that uses Structured Search‑Process Memory to improve factor discovery. Instead of storing only final factors or full search trajectories, it records reusable evidence about which edit motifs succeed or fail in specific parent‑factor contexts, extracted from Abstract Syntax Tree differences. The system incorporates confidence‑gated residual memory, a search‑ledger prior, and asymmetric veto control to suppress high‑confidence failure patterns, leading to better out‑of‑sample performance and fixed‑budget discovery efficiency on CSI 500 and S&P 500 datasets.
By Hang Yu, Zifan Zheng, Chun Gan, Jeff Z. Pan, Tongliang Liu, Zhiyong Wang, Fengxiang He
arXiv:2607. 26642v1 Announce Type: new Abstract: Automated alpha mining has increasingly adopted large language model (LLM) agents for factor generation and iterative discovery.
By Jingyang Yi, Jian Yang, Yifei Jin, Yuqi Li, Jian Li
Automated alpha mining has increasingly adopted large language model (LLM) agents for factor generation and iterative discovery. However, existing LLM-based systems often delegate both factor construction and search decisions to the agent itself, without an explicit exploration space or a principled mechanism for navigating that space.
arXiv:2508. 13174v2 Announce Type: replace Abstract: Formula alpha mining, which generates predictive signals from financial data, is critical for quantitative investment.
By Hongjun Ding, Binqi Chen, Jinsheng Huang, Taian Guo, Zhengyang Mao, Guoyi Shao, Lutong Zou, Luchen Liu, Ming Zhang
arXiv:2608.28632v1 Announce Type: new
Abstract: Large language model agents can discover alphas, yet current methods have three weaknesses. The search cannot adapt during the run, automation usually...
By Zongqian Li, Yaoyiran Li, Yaohui Guo, Ming Zhang, Nigel Collier, Eugene Ie
arXiv:2608. 12841v1 Announce Type: cross Abstract: We study recursive self-improvement at the level of quantitative-investment research: whether an autonomous system can use evidence from earlier experiments to improve the hypotheses and candidates proposed in later iterations.
By Jiacheng Guo, Suozhi Huang, Yunlong Gao, Zihao Li, Jian Ge, Xu Kuang, Mengdi Wang
arXiv:2603.16365v3 Announce Type: replace
Abstract: We study alpha factor mining, the automated discovery of predictive signals from noisy, non-stationary market data-under a practical requirement th...
By Qinhong Lin, Ruitao Feng, Yinglun Feng, Zhenxin Huang, Yukun Chen, Zhongliang Yang, Linna Zhou, Binjie Fei, Jiaqi Liu, Yu Li
arXiv:2610.14959v2 Announce Type: new
Abstract: Formulaic alpha mining seeks to discover executable expressions that capture predictive market signals in a vast, noisy search space. Recent LLM-based...
By Jie Huang, Yuecheng Hong, Yao Chen, Hao Zhong, Linfeng Xiao, Xudong Liu, Hao Xia, Jianxuan Xin
arXiv:2610.17130v2 Announce Type: new
Abstract: Automated alpha factor discovery is critical for modern quantitative research. While large language models (LLMs) have increasingly been integrated int...
By Haolin Yang, Zhiqiang Qian, Chutian Chen, Jipeng Zhang, Zhenghao Zhu, Tangjia Deng, Jian Xie, Shuaishuai Gong, Yike Guo, Sirui Han
arXiv:2608. 11250v1 Announce Type: new Abstract: Language models can propose many plausible trading factors, but an autonomous research system must also allocate its evaluation budget, verify its own evidence, and preserve how each candidate was produced.
By Weicheng Ye, Youran Sun, Xingyu Ren, Shunyao Yu, Chugang Yi, Haizhao Yang
arXiv:2606. 29194v1 Announce Type: new Abstract: Automated alpha mining holds the scoring function fixed and varies the search algorithm over it.
By Yuqi Li, Siyuan Liu, Bingjun Liu