Foundations of Stock Analysis and Backtesting with Python

Ready to move beyond basic stock charts and use data to inform your investment decisions? This course provides a practical introduction to quantitative stock analysis, empowering you to test your ideas systematically with Python. You will learn the complete workflow of a quantitative analyst, from gathering financial data to evaluating a trading strategy. By the end, you'll be able to programmatically source market data, perform key calculations, visualize trends, and build a simple backtesting engine from scratch to measure strategy performance. What you'll learn: - Learn Python fundamentals for data analysis with the pandas library. - Practice fetching and cleaning historical stock price data using web APIs. - Analyze time-series data to calculate returns, volatility, and common technical indicators. - Create clear visualizations of stock performance and financial metrics. - Build a complete backtesting engine to simulate and evaluate a trading strategy. - Understand the core principles of risk, return, and strategy validation. - Apply modern development practices like using virtual environments for your projects. The curriculum starts with the basics of Python and pandas for data manipulation, then progresses to real-world financial analysis techniques. You will apply these skills to build and run a backtesting simulation step-by-step. This course is designed for absolute beginners. No prior experience in programming or financial analysis is required to get started. Begin your journey into the world of data-driven trading today.