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Alpha-GPT: Human-AI Interactive Alpha Mining for Quantitative Investment

Author

Listed:
  • Saizhuo Wang
  • Hang Yuan
  • Leon Zhou
  • Lionel M. Ni
  • Heung-Yeung Shum
  • Jian Guo

Abstract

One of the most important tasks in quantitative investment research is mining new alphas (effective trading signals or factors). Traditional alpha mining methods, either hand-crafted factor synthesizing or algorithmic factor mining (e.g., search with genetic programming), have inherent limitations, especially in implementing the ideas of quants. In this work, we propose a new alpha mining paradigm by introducing human-AI interaction, and a novel prompt engineering algorithmic framework to implement this paradigm by leveraging the power of large language models. Moreover, we develop Alpha-GPT, a new interactive alpha mining system framework that provides a heuristic way to ``understand'' the ideas of quant researchers and outputs creative, insightful, and effective alphas. We demonstrate the effectiveness and advantage of Alpha-GPT via a number of alpha mining experiments.

Suggested Citation

  • Saizhuo Wang & Hang Yuan & Leon Zhou & Lionel M. Ni & Heung-Yeung Shum & Jian Guo, 2023. "Alpha-GPT: Human-AI Interactive Alpha Mining for Quantitative Investment," Papers 2308.00016, arXiv.org.
  • Handle: RePEc:arx:papers:2308.00016
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    File URL: http://arxiv.org/pdf/2308.00016
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    References listed on IDEAS

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    1. Andrew W. Lo & Harry Mamaysky & Jiang Wang, 2000. "Foundations of Technical Analysis: Computational Algorithms, Statistical Inference, and Empirical Implementation," Journal of Finance, American Finance Association, vol. 55(4), pages 1705-1765, August.
    2. Shuo Yu & Hongyan Xue & Xiang Ao & Feiyang Pan & Jia He & Dandan Tu & Qing He, 2023. "Generating Synergistic Formulaic Alpha Collections via Reinforcement Learning," Papers 2306.12964, arXiv.org.
    3. Tianping Zhang & Yuanqi Li & Yifei Jin & Jian Li, 2020. "AutoAlpha: an Efficient Hierarchical Evolutionary Algorithm for Mining Alpha Factors in Quantitative Investment," Papers 2002.08245, arXiv.org, revised Apr 2020.
    4. Selim Amrouni & Aymeric Moulin & Jared Vann & Svitlana Vyetrenko & Tucker Balch & Manuela Veloso, 2021. "ABIDES-Gym: Gym Environments for Multi-Agent Discrete Event Simulation and Application to Financial Markets," Papers 2110.14771, arXiv.org.
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    Cited by:

    1. Alejandro Lopez-Lira & Jihoon Kwon & Sangwoon Yoon & Jy-yong Sohn & Chanyeol Choi, 2025. "Bridging Language Models and Financial Analysis," Papers 2503.22693, arXiv.org.

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