This comprehensive guide takes you from your very first lines of Python code to building and backtesting advanced algorithmic trading systems. Designed for traders, quants, and developers alike, Algorithmic Trading: From Beginner to Advanced blends financial theory, coding practice, and professional-grade strategy development into one cohesive learning journey.

Starting with the fundamentals of markets, risk, and OHLCV data, you'll quickly learn to use Python for downloading, analyzing, and visualizing real market data. The book then introduces you to Backtrader ? the powerful open-source backtesting framework ? and walks you through creating, testing, and refining strategies step by step.

Each chapter builds on the previous one, culminating in a diverse collection of sophisticated trading systems: trend-following models with regime filters, momentum ignition setups, mean-reversion frameworks, volatility breakouts, and even hybrid strategies enhanced by machine learning. You'll also learn how to conduct rolling and walk-forward backtests, implement dynamic position sizing, and stress-test your portfolio under extreme scenarios.

Whether you're learning to automate your first strategy or advancing toward professional quant research, this book gives you the clarity, structure, and ready-to-run Python code you need to trade smarter and build resilient algorithmic systems.