Understanding how your portfolio moves with the market—or against it—is key to managing risk and return effectively. In this post, we’ll dive into two powerful metrics using Python: Beta, which measures your portfolio’s sensitivity to market movements, and Dollar Delta, which quantifies the dollar impact of those movements. We’ll also calculate portfolio volatility and market correlation for…
Risk management is the shield that protects your portfolio from unexpected losses. Whether it’s a sudden market dip or a prolonged downturn, understanding and quantifying risk is essential for any investor. In this post, we’ll explore three practical techniques—Value at Risk (VaR), Conditional VaR (CVaR), and stress testing—and bring them to life using Python with…
Portfolio theory is a powerful framework that helps investors balance risk and return by constructing optimal portfolios. In this second post in the series portfolio management with Python, we’ll dive into its core ideas—diversification, correlation, and the Efficient Frontier—building on the basics from Post 1. Using Python and real-world stock data from Apple (AAPL), Microsoft…
Portfolio management is a crucial skill for any investor, whether you’re managing your own savings or working in finance. At its core, portfolio management is about balancing risk and return to achieve your financial goals. With the rise of powerful tools like Python, even beginners can dive into this world and start analyzing real-world data…