Abstract
This study examines the performance of Artificial Intelligence Exchange Traded Funds in the U.S. While Artificial Intelligence focuses on the creation of intelligence that functions like human, an Artificial Intelligence (AI) Exchange Traded Fund (ETF) is an investment fund seeking to benefit from increased adoption and utilization of AI, including funds that specifically invest in companies involved in AI related new development and funds that utilize AI methodologies to select investment securities. We investigate the performance of all AI ETFs traded in the U.S. from June 2005 to May 2025. Our empirical results suggest that AI ETFs with investment targets related to AI development perform better than the overall market in the past two decades, but the difference is not statistically significant. On the other hand, AI ETFs that utilize AI methodologies to choose investment securities under-perform the market in the past two decades and the difference is statistically significant. However, the performance of the under-performing AI ETFs have improved over time. Market has a significant impact on AI ETF returns, while interest rate has not. AI ETFs with lower expense ratios tend to provide higher return. In addition, there is short-term daily momentum in AI ETF returns. The return persistence disappears in monthly returns. As the literature about the performance of AI application in investments is scarce, we hope to have shed some light in the area and encourage more study on AI related investments.
Presenters
Tzu-Man HuangProfessor, Department of Accounting and Finance, California State University, Stanislaus, California, United States
Details
Presentation Type
Paper Presentation in a Themed Session
Theme
KEYWORDS
Artificial Intelligence, Exchange Traded Funds, AI methodologies, ETF performance
