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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

Technical analysis – ideal for computing, but missing real market processes

The main idea that lies in the foundation of technical analysis, or TA for short, is that price includes everything in itself. From this standpoint, if we see a price movement up or down, large or small, we don’t really want to know the reason behind this movement; instead, we just acknowledge that it was caused by some fundamental factors and try to focus on the future price development in regard to the observed price movement only.

Of course, TA can analyze a series of data and not just a single data point. In this regard, TA studies help in identifying patterns or repeating sequences in price time series that bear resemblance to each other. TA suggests that if we observe a pattern that we already saw in the past, then the following price development will also be similar to what happened in the past; therefore, we can be prepared and exploit it.

With TA, we don’t want and don’...

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