THE ROLE OF ARTIFICIAL INTELLIGENCE IN INVESTMENT PERFORMANCE: A COMPARATIVE ANALYSIS OF TRADITIONAL AND AI-ASSISTED PORTFOLIO STRATEGIES

In this context, this research assesses if the application of AI can contribute to better investment results than conventional portfolio management approaches. With data from four sectors of the S&P 500 sector ETFs, including technology (XLK), financial (XLF), healthcare (XLV), and energy (XLE), the paper contrasts an equally weighted portfolio with a portfolio aided by dynamic rebalancing using AI over the period of 2021-2025. The comparison of the two portfolios is based on four criteria: annualized returns, volatility, Sharpe ratio, and maximum drawdown. According to findings, the dynamically rebalanced portfolio outperformed the former with a higher Sharpe ratio (0.96 vs. 0.74), a lower maximum drawdown (-15.1% vs. -18.2%), and higher returns (14.7% vs. 12.1%).