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

Money management and multiple entries

To give you an idea about what money management is and how it may affect strategy performance, let me tell you about probably the most famous – or infamous – kind of money management technique, known as martingale.

The origin of martingale is in gambling. Imagine the simplest gambling game of a coin toss. You toss the coin and if it comes up heads, you win; if it comes up tails, you lose. We can use 1 for wins and -1 for losses and the series of tosses can be represented by a sequence as follows:

S = {1, -1, -1, 1, -1, 1, 1, 1, -1, -1, 1, -1, ...}

If you put at stake an equal amount of money each time you toss the coin, we can multiply the sequence by that amount and write it like so:

S1 = {b, -b, -b, b, -b, b, b, b, -b, -b, b, -b, ...}

Here, b refers to the size of the bet. Obviously, your total win in the game is the sum of the entire series. In an idealistic model, the results of each toss are independent of each...