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.

本文提出一种新的 alpha 挖掘范式，通过引入人工智能与人类互动，并结合大型语言模型的力量，构建了 Alpha-GPT 交互式 alpha 挖掘系统框架，以一种启发式方式理解量化研究人员的想法，并输出创造性、有洞察力和有效的 alpha。通过多个 Alpha 挖掘实验，证明了 Alpha-GPT 的有效性和优势。