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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

Retrieving data – garbage in, garbage out

The FIX protocol is universal by design and thus can be used not only for ordering but also for data retrieval. However, in most cases, it is not actually used for market data transfer; instead, trading venues provide their own proprietary APIs to retrieve data from there.

As always, in this gloomy world of communication protocols, everything is individual and each trading venue offers its own API. However, in general, all broker APIs are implemented as REST or Websockets. The former is convenient for occasional requests for quotes, while the latter is best for continuous subscriptions that allow receiving real-time market data.

The following examples I provide are taken from the API of LMAX, one of the key ECNs in the FX market. They are not only great because of their openness to any client, big or small, but also because they are one of the very few trading venues that publicly disseminate real-time market data – and...

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