Foundations of Trading Strategy Backtesting

Have you ever wondered if your trading ideas would actually perform well in the real market? Backtesting allows you to test your strategies using historical market data before risking any real capital. This text-based course guides you through the core principles of strategy backtesting, helping you transition from guessing to making data-supported decisions. You will understand how to analyze performance metrics, avoid common statistical traps, and systematically evaluate your trading rules. What you'll learn: - Understand the core principles, terminology, and mechanics of backtesting trading strategies. - Analyze historical market data to evaluate entry and exit signals. - Identify and avoid common pitfalls like overfitting, look-ahead bias, and survivorship bias. - Calculate key performance metrics including Sharpe ratio, maximum drawdown, and win rate. - Apply modern data analysis concepts using Python and standard libraries to automate your testing. - Design structured rules to systematically manage risk and capital allocation. The course starts with essential terminology and the foundational theory of historical testing. You will then progress through step-by-step written walkthroughs that demonstrate how to structure a backtest, process historical data, and interpret performance results. This course is designed for beginner traders, analysts, and finance enthusiasts who want to learn systematic strategy evaluation. No prior programming or advanced trading experience is required. Start reading today to build a disciplined, data-backed approach to your trading strategies.