Opis
Most Python trading books teach libraries in isolation. This book teaches you the complete workflow professionals use to build systematic strategies. The book walks you through the complete journey. You start by acquiring and cleaning market data, handling the messy realities of missing values and misaligned time series. With clean data in hand, you move into exploration: visualizing market relationships, forming trading hypotheses, and identifying patterns worth pursuing. Signal generation follows naturally from that analysis. You build indicators, define entry and exit rules, then validate everything through rigorous backtesting using walk-forward analysis and out-of-sample testing. The final stage: evaluating performance with institutional-grade metrics and deploying your strategy for automated execution.This entire process is demonstrated through one volatility tail-hedge strategy, built progressively across every chapter. Same data, same strategy, layer by layer. You see how each step connects to the next. You'll learn professional standards developed over 25 years of institutional trading: spotting lookahead bias, structuring production code, validating backtests, and distinguishing real edges from noise. All code included.
By the end, you have a working strategy and a repeatable framework for building your own.