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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

Summary

Let’s quickly recap what we learned in this chapter. It indeed is the ultimate point where all the knowledge and skills we obtained in previous chapters unite and transform into a working trading application. More than that, in fact, we’ve got now a scalable trading platform suitable for both research and live trading. We suggested a robust design of the platform that keeps the architecture modular and scalable. We learned how to synchronize threads to ensure the correct order of execution of the platform modules while keeping these modules isolated. We saw practical examples of using various data sources that allow the platform to work with both live data feeds and historical data. We completely isolated the trade logic from the rest of the app so now we can develop a strategy using a backtest and then immediately copy and paste the code into the production version of our platform. Finally, using our knowledge of FX markets from previous chapters, we developed...

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