The Investment Styles and Performance of AI-Related ETFs: Analyzing the Impact of Active Management
Year: 2025
Type: article
Abstract: This paper studies the performance of ETFs that invest in companies involved in artificial intelligence (AI) technologies, such as firms focused on AI research, development, and applications. Using daily data from 15 American ETFs focused on AI-related companies over the period from 1 February 2019 to 29 December 2023, this paper investigates their investment style characteristics through a returns-based style analysis (RBSA). This study offers detailed insights into the degree of active versus passive management and highlights strategic patterns that may guide investment decisions in AI-themed financial products. We highlight that asset selection drives fund performances more than active management strategies, offering practical insights for investors and policymakers.
Source: FinTech
Authors: Nikoletta Poutachidou, Alexandros Koulis
Institutions: University of Thessaly, Hellenic Open University
Language: English
Subfield: Finance
Domain: Social Sciences
Open Access status: gold
Estimated APC paid: $1,207
OpenAlex ID: W4410863606