2024/02/15 by Hang Yuan, Yuan, Hang, Saizhuo Wang +3 · 6 citations
Decision Sciences · #Artificial Intelligence (cs.AI) #Computational Finance (q-fin.CP) #FOS: Computer and information sciences #FOS: Economics and business #Stock Market Forecasting Methods
paper · pdf · doi:10.48550/arxiv.2402.09746
openalex publication_date 2024/02/15 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
Recently, we introduced a new paradigm for alpha mining in the realm of quantitative investment, developing a new interactive alpha mining system framework, Alpha-GPT. This system is centered on iterative Human-AI interaction based on large language models, introducing a Human-in-the-Loop approach to alpha discovery. In this paper, we present the next-generation Alpha-GPT 2.0 \footnoteDraft. Work in progress, a quantitative investment framework that further encompasses crucial modeling and analysis phases in quantitative investment. This framework emphasizes the iterative, interactive research between humans and AI, embodying a Human-in-the-Loop strategy throughout the entire quantitative investment pipeline. By assimilating the insights of human researchers into the systematic alpha research process, we effectively leverage the Human-in-the-Loop approach, enhancing the efficiency and precision of quantitative investment research.