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

ArXiv ID: 2308.00016 “View on arXiv”

Authors: Unknown

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.

Keywords: alpha mining, prompt engineering, Large Language Models (LLMs), human-AI interaction, Quantitative Investment

Complexity vs Empirical Score

• Math Complexity: 4.0/10
• Empirical Rigor: 7.5/10
• Quadrant: Street Traders
• Why: The paper introduces a novel interactive alpha mining paradigm and an agentic workflow with specific components (Trading Idea Polisher, Quant Developer, Analyst) and mentions backtesting metrics like IC and Sharpe ratio, demonstrating significant implementation and empirical validation. However, the core methodology focuses on prompt engineering and system architecture using LLMs rather than dense theoretical derivations or advanced mathematics.

  flowchart TD
    A["Research Goal:<br>Alpha Mining Paradigm Shift"] --> B["Input: Human Quant Ideas<br>+ Financial Data"]
    B --> C["Method: Prompt Engineering<br>with LLMs"]
    C --> D["Process: Interactive<br>Human-AI Co-Creation"]
    D --> E{"Outcome: Alpha-GPT System"}
    E --> F["Output: Creative,<br>Insightful Alphas"]
    F --> G["Result: Improved<br>Investment Signals"]