Transforming Investment Strategies: AI-Driven Portfolio Optimization

Abstract

AI has transformed the approach to delivering financial services significantly with its ease of decision-making and risk control. The paper investigates how AI influences portfolio management by analysing, practical data and distinct models such as support vector machines (SVM), artificial neural networks (ANN), and reinforcement learning (RL). The effectiveness of these models is                                                                                    assessed relative to typical approaches such as Mean-Variance Optimization (MVO) with measures including return on investment (ROI), Sharpe ratio and maximum loss. Findings reveal that AI-inspired models bring large positive impacts on risk-adjusted outcomes as well as adjusting to new markets and personalizing portfolios. The research discusses significant challenges and ethical concerns that arise when AI operates in financial markets.