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Alpha-GPT 2.0: Human-in-the-Loop AI for Quantitative Investment

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arxiv 2402.09746 v1 pith:YLEKF6IC submitted 2024-02-15 q-fin.CP cs.AI

Alpha-GPT 2.0: Human-in-the-Loop AI for Quantitative Investment

classification q-fin.CP cs.AI
keywords investmentquantitativealphahuman-in-the-loopalpha-gptframeworkresearchapproach
verification ladder T0 review T1 audit T2 compute T3 formal T4 reserved
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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 \footnote{Draft. 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.

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