Book Image

Getting Started with Forex Trading Using Python

By : Alex Krishtop
Book Image

Getting Started with Forex Trading Using Python

By: Alex Krishtop

Overview of this book

Algorithm-based trading is a popular choice for Python programmers due to its apparent simplicity. However, very few traders get the results they want, partly because they aren’t able to capture the complexity of the factors that influence the market. Getting Started with Forex Trading Using Python helps you understand the market and build an application that reaps desirable results. The book is a comprehensive guide to everything that is market-related: data, orders, trading venues, and risk. From the programming side, you’ll learn the general architecture of trading applications, systemic risk management, de-facto industry standards such as FIX protocol, and practical examples of using simple Python codes. You’ll gain an understanding of how to connect to data sources and brokers, implement trading logic, and perform realistic tests. Throughout the book, you’ll be encouraged to further study the intricacies of algo trading with the help of code snippets. By the end of this book, you’ll have a deep understanding of the fx market from the perspective of a professional trader. You’ll learn to retrieve market data, clean it, filter it, compress it into various formats, apply trading logic, emulate the execution of orders, and test the trading app before trading live.
Table of Contents (21 chapters)
1
Part 1: Introduction to FX Trading Strategy Development
5
Part 2: General Architecture of a Trading Application and A Detailed Study of Its Components
11
Part 3: Orders, Trading Strategies, and Their Performance
15
Part 4: Strategies, Performance Analysis, and Vistas

Trading app architecture – revised and improved

In Chapter 1, Developing Trading Strategies – Why They Are Different, we proposed a generalized architecture of a trading application. In brief, it consists of the following components:

  • Data receiver: Something that retrieves live data from the market or historical data stored locally; see Chapter 5, Retrieving and Handling Market Data with Python
  • Data cleanup: A component that eliminates non-market prices; see Chapter 1, Developing Trading Strategies – Why They Are Different
  • Trading logic: The brains of the trading app that make trading decisions (see Chapter 6, Basics of Fundamental Analysis and Its Possible Use in FX Trading, Chapter 7, Technical Analysis and Its Implementation in Python, and Chapter 9, Trading Strategies and Their Core Elements), frequently with integrated pre-trade risk management
  • Ordering interface: A component that receives trading signals from the trading logic, converts...