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%).本研究旨在评估人工智能（AI）的应用能否取得优于传统投资组合管理方法的投资业绩。本文采用标普500（S&P 500）行业交易所交易基金（ETF）四大板块的数据，涵盖科技（XLK）、金融（XLF）、医疗保健（XLV）与能源（XLE）四个领域，并在2021年至2025年的时间跨度内，对比了等权重投资组合与借助AI动态再平衡辅助的投资组合的表现。两项投资组合的对比基于四项评价指标：年化收益率、波动率、夏普比率（Sharpe ratio）与最大回撤（maximum drawdown）。研究结果显示，借助AI动态再平衡的投资组合表现更优：其夏普比率更高（0.96 vs 0.74）、最大回撤更低（-15.1% vs -18.2%）且年化收益率更高（14.7% vs 12.1%）。