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Getting Started with Forex Trading Using Python

Getting Started with Forex Trading Using Python

By : Alex Krishtop
4.3 (3)
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Getting Started with Forex Trading Using Python

Getting Started with Forex Trading Using Python

4.3 (3)
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)
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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

The advantages of using Python in trading strategy development

Today when we say Python, we most likely mean not only the most flexible object-oriented programming language but also the most powerful and convenient interactive IDEs, such as Spyder or PyCharm, along with the vast collection of libraries that extend this language to fit virtually any domain of applied and fundamental research, from medicine to astronomy. There is no surprise that the Python ecosystem has become the de facto standard in the financial industry where numbers play a decisive role.

The advantages of using Python for the development of trading strategies are obvious and we will look into a few of these advantages in detail in the following sections.

Memory management

Python is one of the few interpreters that has robust built-in memory management services such as garbage collection and reference counting. Essentially, this means that you don’t have to care about any complex object you work...

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