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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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Toc

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

Part 2: General Architecture of a Trading Application and A Detailed Study of Its Components

Being familiar with the subject domain is essential for any software development, and Part 1 introduced the basics of the FX market and the key features typical of trading applications. Now, it’s time to outline the architecture of such an application and consider its main components in greater detail.

Part 2 suggests several solutions used to retrieve and handle market data, explains the difference between fundamental and technical analysis, focuses on the meaning of classical technical analysis (TA) indicators from a market process standpoint, and provides possible implementations of these indicators in Python, in a way compatible with further developments. We will also familiarize ourselves with the basics of simple data visualization, which is typically used to quickly check market data and the correctness of calculations, and generate entry and exit orders.

This part comprises...

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