mlsanityData to 7 Oct 2026

ChatGPT-based Investment Portfolio Selection

arXiv 2308.06260 ↗First posted 11 Aug 2023q-fin.PM cs.AI cs.CEcited by 8

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Abstract (arXiv)

In this paper, we explore potential uses of generative AI models, such as ChatGPT, for investment portfolio selection. Trusting investment advice from Generative Pre-Trained Transformer (GPT) models is a challenge due to model "hallucinations", necessitating careful verification and validation of the output. Therefore, we take an alternative approach. We use ChatGPT to obtain a universe of stocks from S&P500 market index that are potentially attractive for investing. Subsequently, we compared various portfolio optimization strategies that utilized this AI-generated trading universe, evaluating those against quantitative portfolio optimization models as well as comparing to some of the popular investment funds. Our findings indicate that ChatGPT is effective in stock selection but may not perform as well in assigning optimal weights to stocks within the portfolio. But when stocks selection by ChatGPT is combined with established portfolio optimization models, we achieve even better results. By blending strengths of AI-generated stock selection with advanced quantitative optimization techniques, we observed the potential for more robust and favorable investment outcomes, suggesting a hybrid approach for more effective and reliable investment decision-making in the future.

Key facts. Cited by 8 papers in the map (data through 7 Oct 2026). Builds on 3 of its 25 references that are in the map. First posted on arXiv 11 Aug 2023.

Builds on

3 of 25 references.

References · 3

  1. 2023GPT-4 Technical Reportcited by 18,132
  2. 2016CVXPY: A Python-Embedded Modeling Language for Convex Optimizationcited by 633
  3. 2023Can ChatGPT Forecast Stock Price Movements? Return Predictability and Large Language Modelscited by 125

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Citing papers per year: 2024: 3; 2025: 5.

8 papers.