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Backtesting Masterclass: Build, Validate, and Optimize with Python: Build Trading Strategies That Actually Work, Then Prove It with Code
Reactive Publishing
The Backtesting Build, Validate, and Optimize with PythonBy Hayden Van Der Post
Ideas are cheap. Verified performance is priceless.
In the algorithmic trading world, strategy means nothing without proof. The Backtesting Masterclass gives you the full-stack tools, frameworks, and insights to rigorously test, validate, and refine your ideas—before putting real money on the line.
Written for quantitative traders, data-driven investors, and Python developers, this book bridges the gap between theory and execution, teaching you how to simulate realistic trading environments and avoid the hidden traps of overfitting, false signals, and unrealistic assumptions.
What You’ll Build Your Own Backtesting Engine: Create fast, modular frameworks in Python using Pandas, NumPy, and vectorized execution
Validate Strategy Performance: Use Sharpe, Sortino, drawdown, and advanced metrics that matter to real-world capital
Avoid Overfitting & Survivorship Bias: Learn cross-validation techniques, walk-forward analysis, and robust performance testing
Incorporate Real Market Frictions: Slippage, commissions, bid-ask spreads, order latency, and how to simulate them accurately
Optimize Without Curve Fitting: Learn hyperparameter tuning, risk-based portfolio allocation, and trade filtering techniques
Run Monte Carlo Simulations: Test thousands of alternate realities and build statistical confidence in your edge
Who This Book Is traders and data scientists building Python-based trading systems
Financial engineers validating models before live deployment
Prop traders, fintech devs, and portfolio managers seeking reproducible edge
Anyone tired of relying on untested trading advice and looking for proof-driven execution
Before you risk your capital, test your strategy like your future depends on it.
Because it does.
The Backtesting Build, Validate, and Optimize with PythonBy Hayden Van Der Post
Ideas are cheap. Verified performance is priceless.
In the algorithmic trading world, strategy means nothing without proof. The Backtesting Masterclass gives you the full-stack tools, frameworks, and insights to rigorously test, validate, and refine your ideas—before putting real money on the line.
Written for quantitative traders, data-driven investors, and Python developers, this book bridges the gap between theory and execution, teaching you how to simulate realistic trading environments and avoid the hidden traps of overfitting, false signals, and unrealistic assumptions.
What You’ll Build Your Own Backtesting Engine: Create fast, modular frameworks in Python using Pandas, NumPy, and vectorized execution
Validate Strategy Performance: Use Sharpe, Sortino, drawdown, and advanced metrics that matter to real-world capital
Avoid Overfitting & Survivorship Bias: Learn cross-validation techniques, walk-forward analysis, and robust performance testing
Incorporate Real Market Frictions: Slippage, commissions, bid-ask spreads, order latency, and how to simulate them accurately
Optimize Without Curve Fitting: Learn hyperparameter tuning, risk-based portfolio allocation, and trade filtering techniques
Run Monte Carlo Simulations: Test thousands of alternate realities and build statistical confidence in your edge
Who This Book Is traders and data scientists building Python-based trading systems
Financial engineers validating models before live deployment
Prop traders, fintech devs, and portfolio managers seeking reproducible edge
Anyone tired of relying on untested trading advice and looking for proof-driven execution
Before you risk your capital, test your strategy like your future depends on it.
Because it does.
734 pages, Kindle Edition
Published August 6, 2025
1 person want to read
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