ChatGPT-based Investment Portfolio Selection

25 Pages Posted: 13 Aug 2023

See all articles by Oleksandr Romanko

Oleksandr Romanko

SS&C Technologies - Algorithmics; University of Toronto - Department of Mechanical and Industrial Engineering

Akhilesh Narayan

Indian Institute of Technology Bombay

Roy Kwon

University of Toronto - Department of Mechanical and Industrial Engineering

Date Written: August 11, 2023

Abstract

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.

Keywords: Portfolio optimization, Investment management, Generative AI, ChatGPT

JEL Classification: C45, C53, C61, G10, G11, G12, G17

Suggested Citation

Romanko, Oleksandr and Narayan, Akhilesh and Kwon, Roy, ChatGPT-based Investment Portfolio Selection (August 11, 2023). Available at SSRN: https://ssrn.com/abstract=4538502 or http://dx.doi.org/10.2139/ssrn.4538502

Oleksandr Romanko (Contact Author)

SS&C Technologies - Algorithmics ( email )

80 Lamberton Road
Windsor, CT 06095
United States

HOME PAGE: http://www.ssctech.com

University of Toronto - Department of Mechanical and Industrial Engineering ( email )

5 King's College Road
Toronto, Ontario M5S 3G8
Canada

Akhilesh Narayan

Indian Institute of Technology Bombay ( email )

Mumbai, 400076
India

Roy Kwon

University of Toronto - Department of Mechanical and Industrial Engineering ( email )

5 King's College Road
Toronto, Ontario M5S 3G8
Canada

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