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

Drawdown

According to an article published on CFI (Maximum Drawdown: https://corporate
financeinstitute.com/resources/capital-markets/maximum-drawdown/), “A maximum drawdown (MDD) measures the maximum fall in the value of the investment, as given by the difference between the value of the lowest trough and that of the highest peak before the trough.” We already saw an illustration of the drawdown in Figure 13.4 and it is quite easy to understand. However, real equity curves never look like ideal sine waves used for illustration purposes, so drawdown is not a constant value; it changes over time and these changes also may say a lot about the volatility of returns.

So, we want to calculate a new time series according to the following algorithm:

  1. Let the first (leftmost) data point in the equity curve be the current historical high (maximum).
  2. Compare the next value with the current one.
  3. If the next value is greater than the current, let the next...