Python for Portfolio Construction and Risk Analysis

Modern investment management relies heavily on computational tools to analyze market risk and optimize asset allocation. This course introduces you to the core science of portfolio construction and shows you how to implement these financial theories using Python. You will transition from understanding basic financial metrics to programmatically modeling risk, return, and portfolio optimization. By writing clean, modern Python code, you will gain the practical skills needed to analyze asset performance and build robust investment strategies based on quantitative data. What you'll learn: - Understand the fundamental principles of risk, return, and portfolio theory. - Calculate key financial metrics such as volatility, drawdown, and Sharpe ratios using Python. - Implement modern portfolio optimization techniques, including efficient frontier plotting. - Apply modern Python data libraries and type hinting to write clean, maintainable financial code. - Analyze historical asset data to simulate portfolio performance under various market conditions. The course begins with essential financial terminology and foundational mathematical concepts before guiding you through step-by-step programming exercises. You will progress from simple return calculations to advanced asset allocation models, learning how to structure your financial code effectively. This course is designed for beginners in quantitative finance, data analysts, or Python enthusiasts who want to apply their skills to investment management. No advanced background in finance or programming is required. Start building and analyzing your own quantitative investment models today.