Book Image

Learn Algorithmic Trading

By : Sebastien Donadio, Sourav Ghosh
Book Image

Learn Algorithmic Trading

By: Sebastien Donadio, Sourav Ghosh

Overview of this book

It’s now harder than ever to get a significant edge over competitors in terms of speed and efficiency when it comes to algorithmic trading. Relying on sophisticated trading signals, predictive models and strategies can make all the difference. This book will guide you through these aspects, giving you insights into how modern electronic trading markets and participants operate. You’ll start with an introduction to algorithmic trading, along with setting up the environment required to perform the tasks in the book. You’ll explore the key components of an algorithmic trading business and aspects you’ll need to take into account before starting an automated trading project. Next, you’ll focus on designing, building and operating the components required for developing a practical and profitable algorithmic trading business. Later, you’ll learn how quantitative trading signals and strategies are developed, and also implement and analyze sophisticated trading strategies such as volatility strategies, economic release strategies, and statistical arbitrage. Finally, you’ll create a trading bot from scratch using the algorithms built in the previous sections. By the end of this book, you’ll be well-versed with electronic trading markets and have learned to implement, evaluate and safely operate algorithmic trading strategies in live markets.
Table of Contents (16 chapters)
Title Page

Creating trading strategies that operate on linearly correlated groups of trading instruments

We are going through the process of implementing an example of a pair trading strategy. The first step is to determine the pairs that have a high correlation. This can be based on the underlying economic relationship (for example, companies having similar business plans) or also a financial product created out of some others, such as ETF. Once we figure out which symbols are correlated, we will create the trading signals based on the value of these correlations. The correlation value can be the Pearson's coefficient, or a Z-score.

In case of a temporary divergence, the outperforming stock (the stock that moved up) would have been sold and the underperforming stock (the stock that moved down) would have been purchased. If the two stocks converge by either the outperforming stock...