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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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Toc

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

Building a drawdown and rolling risk analysis

A focus only on returns without considering risk is like driving a fast car at high speeds without a seatbelt—it may work for a while, but the consequences can be catastrophic. Risk metrics provide the analytical framework to quantify and manage uncertainty, which lets traders make more informed decisions. These metrics offer insights into the potential volatility, drawdown, and other adverse conditions a strategy might encounter. By incorporating risk analytics into the trading process, traders can better assess the trade-offs between risk and return, optimize their portfolios for maximum risk-adjusted performance, and establish safeguards to mitigate potential losses.

Pyfolio offers several risk metrics to help maintain control of algorithmic trading systems. We’ll look at several in this recipe.

Getting ready…

We assume the steps in the Preparing Zipline Reloaded backtest results for Pyfolio Reloaded recipe...

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