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

Backtesting – speeding up the research

The process of developing a trading strategy (I mean the trading logic, not the application) is an infinite loop:

  1. Suggest a hypothesis.
  2. Code it.
  3. Run a test.
  4. If the result is not satisfactory, tweak the parameters and repeat.
  5. If nothing helps, look for an alternative hypothesis.

The question is: what kind of application shall we use for testing in step 3?

Of course, we could use our existing trading app, draft some strategy logic, and then run it in test mode, as we’ve just done, collecting orders and analyzing the equity time series. But then a single test may take days, weeks, and even months if we want to test the strategy under different market conditions. Do you think it’s a bit too long? I agree. That’s why, for research and development purposes, we use backtesting.

We discussed backtesting in Chapter 2, Using Python for Trading Strategies, in the Paper trading, and backtesting...