  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.
