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

• URL: http://arxiv.org/abs/2308.00016v1
• Date: Mon, 31 Jul 2023 16:40:06 GMT
• Title: Alpha-GPT: Human-AI Interactive Alpha Mining for Quantitative Investment
• Authors: Saizhuo Wang, Hang Yuan, Leon Zhou, Lionel M. Ni, Heung-Yeung Shum, Jian Guo
• Abstract summary: We propose a new alpha mining paradigm by introducing human-AI interaction. We also develop Alpha-GPT, a new interactive alpha mining system framework.
• Score: 9.424699345940725
• License: http://creativecommons.org/licenses/by/4.0/
• 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.

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