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

About

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.

Saizhuo Wang, Hang Yuan, Leon Zhou, Lionel M. Ni, Heung-Yeung Shum, Jian Guo• 2023

Related benchmarks

TaskDatasetResultRank
Factor DiscoveryTushare Pro A-share (2022-2026)
Yield9.1
20
Alpha MiningCSI500 (test)
IC (Information Coefficient)0.0077
19
Alpha MiningS&P 500 2022-01-01 to 2025-12-26 (test)
IC0.0163
10
Symbolic RegressionLLM-SRBench Transform
Median R21.253
3
Factor DiscoveryA-share market data
Accepted Count9
3
Symbolic RegressionLLM-SRBench Synthetic
Median R20.757
3
Symbolic RegressionLLM-SRBench Overall
Median R20.12
3
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