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

Data compression – keeping the amounts to a reasonable minimum

In the previous section, we already considered one of the most popular data compression techniques used by data providers: snapshots. The difference is that a tick represents a single event (such as a new trade or a change in bid or ask) and a single price value, but a snapshot instead discards information about individual ticks and replaces it with the following prices per period:

  • Price of the first tick of the period (or open)
  • Maximum price for the period (or high)
  • Minimum price for the period (or low)
  • Price of the last tick of the period (or close)

For example, if the period is 1 minute and during this minute 100 trades were placed, then the snapshot will replace 100 ticks (or 100 prices) with just 4 prices.

The resulting snapshots are called bars when plotted on charts. Very frequently, traders and developers use bars instead of snapshots. Graphically, a bar is typically presented...