Stock portfolio selection based on risk appetite: Evidence from ChatGPT

Schneider, J, Constantin; Yilmaz, Yahya


Abstract

We analyze whether a large language model can generate investment portfolios with varying risk appetites and evaluate their performance against benchmarks. We prompt different ChatGPT models to create portfolios for different risk appetites of retail investors, focusing on U.S. and European equity markets. Our study reveals that higher-risk portfolios yield higher returns. GPT-4o outperforms in the U.S., while GPT-4 offers the highest returns in Europe. We further show that ChatGPT effectively adjusts portfolio risk and return metrics based on individual risk preferences. These findings suggest private investors can use ChatGPT to improve investment decisions, but careful model selection is vital.

Keywords
Large language model; ChatGPT; Information processing; Financial advice; Asset selection; Stock picking; Investment



Publication type
Research article (journal)

Peer reviewed
Yes

Publication status
Published

Year
2025

Journal
Finance Research Letters

Volume
82

Language
English

ISSN
1544-6123

DOI

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