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Getting Started with Forex Trading Using Python

You're reading from   Getting Started with Forex Trading Using Python Beginner's guide to the currency market and development of trading algorithms

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Product type Paperback
Published in Mar 2023
Publisher Packt
ISBN-13 9781804616857
Length 384 pages
Edition 1st Edition
Languages
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Author (1):
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Alex Krishtop Alex Krishtop
Author Profile Icon Alex Krishtop
Alex Krishtop
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Table of Contents (21) Chapters Close

Preface 1. Part 1: Introduction to FX Trading Strategy Development
2. Chapter 1: Developing Trading Strategies – Why They Are Different FREE CHAPTER 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

Optimization – the blessing and the curse of algo trading

Do you remember how the performance of a simple overnight strategy that we created earlier in this chapter radically changed when we replaced a tight stop of 5 pips with a wider stop of 50 pips?

But this fact raises another important question: why 5 and 50 pips? Why not 6 and 45? Or 10 and 76?

Any quantitative strategy depends on the values of its parameters, and the procedure of finding the best combination of parameters that delivers the best results of the backtesting is called optimization.

Optimization is a massive topic. I’d even say it’s overwhelmingly vast and complex. At first glance, it looks straightforward: let’s find the best combination of parameter values and then run the strategy live with these very values. However, the problem is that we always test and optimize our strategies using past data. And I hope you already understood and remember well that markets are anything...

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