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Python for Algorithmic Trading Cookbook

You're reading from   Python for Algorithmic Trading Cookbook Recipes for designing, building, and deploying algorithmic trading strategies with Python

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Product type Paperback
Published in Aug 2024
Publisher Packt
ISBN-13 9781835084700
Length 404 pages
Edition 1st Edition
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Author (1):
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Jason Strimpel Jason Strimpel
Author Profile Icon Jason Strimpel
Jason Strimpel
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Table of Contents (16) Chapters Close

Preface 1. Chapter 1: Acquire Free Financial Market Data with Cutting-Edge Python Libraries FREE CHAPTER 2. Chapter 2: Analyze and Transform Financial Market Data with pandas 3. Chapter 3: Visualize Financial Market Data with Matplotlib, Seaborn, and Plotly Dash 4. Chapter 4: Store Financial Market Data on Your Computer 5. Chapter 5: Build Alpha Factors for Stock Portfolios 6. Chapter 6: Vector-Based Backtesting with VectorBT 7. Chapter 7: Event-Based Backtesting Factor Portfolios with Zipline Reloaded 8. Chapter 8: Evaluate Factor Risk and Performance with Alphalens Reloaded 9. Chapter 9: Assess Backtest Risk and Performance Metrics with Pyfolio 10. Chapter 10: Set Up the Interactive Brokers Python API 11. Chapter 11: Manage Orders, Positions, and Portfolios with the IB API 12. Chapter 12: Deploy Strategies to a Live Environment 13. Chapter 13: Advanced Recipes for Market Data and Strategy Management 14. Index 15. Other Books You May Enjoy

Event-Based Backtesting Factor Portfolios with Zipline Reloaded

Zipline Reloaded is an event-driven backtesting framework that processes market events sequentially, allowing for more realistic modeling of order execution and slippage. Unlike vector-based frameworks, it accounts for the temporal sequence of market events, making it suitable for complex strategies that involve conditional orders or asset interactions. While generally slower than vector-based approaches, event-based backtesting frameworks tend to better simulate market dynamics making them helpful for path-dependent strategies requiring intricate order logic, state management, and risk management.

Zipline Reloaded is well suited for backtesting large universes and complex portfolio construction techniques. The Pipeline API is designed for high-efficiency computation of factors among thousands of securities. We’ll use Zipline Reloaded to backtest portfolio factor strategies, the results of which can be analyzed...

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