Opportunities and Challenges of Artificial Intelligence in Exchange-Traded Funds: A Quantitative Modelling Approach Using Markowitz Portfolio Theory

This thesis, titled “Opportunities and Challenges of Artificial Intelligence in Exchange-Traded Funds: A Quantitative Modelling Approach Using Markowitz Portfolio Theory”, aims to explore thoroughly the impact of artificial intelligence presence in financial markets, with a specific focus on Exchange-Traded Funds. After a brief yet concise presentation of Exchange-Traded Funds, this paper delves deeper into their role, functioning, and infrastructure, providing insights into their market. Afterwards, this paper lays the foundation for the application of artificial intelligence in the financial industry, with a dedicated emphasis on artificial intelligence-driven algorithmic and high-frequency trading as the main drivers of market crashes. Thereafter a literature review of current US and EU regulations on Exchange-Traded Funds and artificial intelligence, this research concludes by examining the symbiosis between Exchange-Traded Funds and artificial intelligence through the analysis of Exchange-Traded Funds managed by artificial intelligence-based strategies.