Abstract
We examine ChatGPT, a prominent Large Language Model (LLM), in supporting portfolio management with a focus on asset selection and diversification through quantitative methods. We use ChatGPT to select assets from various asset classes and evaluate the diversification effect of its selections. Our results suggest that ChatGPT’s selections are statistically significantly better in diversity index than randomly selected assets. We also construct portfolios based on ChatGPT’s selections and find that they outperform portfolios built on randomly selected assets. Overall, our study contributes to a better understanding of the role of LLMs like ChatGPT as potential assistants for portfolio managers.
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