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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
Languages
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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

Deploying a monthly factor portfolio strategy

We’ll now integrate the momentum factor we built in Chapter 5, Build Alpha Factors for Stock Portfolios, into our trading app. The app is designed to download and process premium U.S. equities data encompassing a comprehensive universe of approximately 20,000 stocks. The advantage of using the premium data is that it lets us build factor portfolios that include the entire universe of U.S.-traded equities.

The trading app is designed to be run on a periodic rebalancing schedule after market hours, typically monthly. Each time it runs, it acquires the latest price data for the entire stock universe. It then computes the momentum factor for these stocks. Based on this computation, the app identifies the top stocks exhibiting the strongest momentum and the bottom stocks showing the weakest momentum. The trading strategy involves going long on the top stocks and short on the bottom stocks.

Our trading app can execute orders that...

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