This course on "The Art of Portfolio Management" explores the intersection of finance, mathematics, business, computer science, and economics in the context of portfolio management. The course is designed to provide the audience with a comprehensive understanding of the theoretical foundations, portfolio construction and optimization techniques, risk management, performance evaluation, and the latest advancements in algorithmic and machine learning approaches to portfolio management. Through an interdisciplinary lens, students will learn to apply mathematical and computational tools to analyze and manage investment portfolios effectively.The course is structured in five acts. The first act introduces the theoretical foundations of portfolio management, covering topics such as Modern Portfolio Theory, Capital Asset Pricing Model, Efficient Market Hypothesis, and Behavioral Finance. The second act delves into portfolio construction and optimization, focusing on risk and return, diversification, asset allocation, and mathematical optimization techniques. The third act discusses risk management and performance evaluation, with an emphasis on various risk assessment methods, benchmarking, and performance metrics. The fourth act explores the cutting-edge algorithmic and machine learning approaches to portfolio management, including AI-driven optimization, natural language processing, and deep learning techniques. The final act addresses ethical considerations, future trends, and global perspectives in portfolio management, encouraging the audience to reflect on the broader implications and potential of their work
