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Getting Started with Forex Trading Using Python

You're reading from  Getting Started with Forex Trading Using Python

Product type Book
Published in Mar 2023
Publisher Packt
ISBN-13 9781804616857
Pages 384 pages
Edition 1st Edition
Languages
Author (1):
Alex Krishtop Alex Krishtop
Profile icon Alex Krishtop

Table of Contents (21) Chapters

Preface 1. Part 1: Introduction to FX Trading Strategy Development
2. Chapter 1: Developing Trading Strategies – Why They Are Different 3. Chapter 2: Using Python for Trading Strategies 4. Chapter 3: FX Market Overview from a Developer's Standpoint 5. Part 2: General Architecture of a Trading Application and A Detailed Study of Its Components
6. Chapter 4: Trading Application: What’s Inside? 7. Chapter 5: Retrieving and Handling Market Data with Python 8. Chapter 6: Basics of Fundamental Analysis and Its Possible Use in FX Trading 9. Chapter 7: Technical Analysis and Its Implementation in Python 10. Chapter 8: Data Visualization in FX Trading with Python 11. Part 3: Orders, Trading Strategies, and Their Performance
12. Chapter 9: Trading Strategies and Their Core Elements 13. Chapter 10: Types of Orders and Their Simulation in Python 14. Chapter 11: Backtesting and Theoretical Performance 15. Part 4: Strategies, Performance Analysis, and Vistas
16. Chapter 12: Sample Strategy – Trend-Following 17. Chapter 13: To Trade or Not to Trade – Performance Analysis 18. Chapter 14: Where to Go Now? 19. Index 20. Other Books You May Enjoy

The basics of charting with Python

There are many libraries that implement charting with Python but at the time of writing, two of them are industry standards – matplotlib and plotly:

  • Matplotlib is the oldest charting library (in heavy use since 2003), which was created in order to bring the well-developed charting facilities of Matlab to Python. It can create charts based on any array-like objects, including native Python lists and numpy arrays, support numerous types of charts, including financial ones (which is what we need!), provides full control over chart objects, features almost unlimited chart customizations, and can be used with different backends.
  • plotly is a relatively young competitor (released in 2014). It offers pretty much the same charting facilities as matplotlib so the choice between the two is not obvious. Plotly definitely wins when it comes to interactivity and working with chart objects via an API but loses the competition in speed and abilities...
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