Algorithmic Trading Strategies: A Practical Guide to Designing, Backtesting, and Automating Profitable Systems

Michael Kessler

Transform emotional gut-feel investing into disciplined algorithmic trading systems that survive real market volatility. Perfect for a focused commute, this analytical guide strips away the hype of easy profits. You will master the exact quantitative...

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Opening Credits

1/10/2026

Chapter 1: From Discretionary Hunches to Systematic Rules

1/10/2026

Chapter 2: Market Mechanics The Terrain Your Algorithms Trade On

1/10/2026

Chapter 3: Strategy Archetypes Turning Ideas into Explicit Rules

1/10/2026

Chapter 4: Data Pipelines Sourcing, Cleaning, and Structuring Market Information

1/10/2026

Chapter 5: From Raw Prices to Signals Feature Engineering and Regime Awareness

1/10/2026

Chapter 6: Designing Honest Tests Backtesting, Validation, and Overfitting Defense

1/10/2026

Chapter 7: From Single Strategy to Robust Portfolio Position Sizing and Risk Control

1/10/2026

Chapter 8: From Backtest to Broker Execution, Slippage, and Infrastructure

1/10/2026

Chapter 9: Keeping the Robot Honest Monitoring, Logging, and Troubleshooting Live Systems

1/10/2026

Chapter 10: Building Your Personal Quant Lab A Realistic Roadmap for Continuous Evolution

1/10/2026

Closing Credits

1/10/2026