Search icon CANCEL
Subscription
0
Cart icon
Your Cart (0 item)
Close icon
You have no products in your basket yet
Arrow left icon
Explore Products
Best Sellers
New Releases
Books
Videos
Audiobooks
Learning Hub
Free Learning
Arrow right icon
Arrow up icon
GO TO TOP
Learn Algorithmic Trading

You're reading from   Learn Algorithmic Trading Build and deploy algorithmic trading systems and strategies using Python and advanced data analysis

Arrow left icon
Product type Paperback
Published in Nov 2019
Publisher Packt
ISBN-13 9781789348347
Length 394 pages
Edition 1st Edition
Languages
Arrow right icon
Authors (2):
Arrow left icon
Sebastien Donadio Sebastien Donadio
Author Profile Icon Sebastien Donadio
Sebastien Donadio
Sourav Ghosh Sourav Ghosh
Author Profile Icon Sourav Ghosh
Sourav Ghosh
Arrow right icon
View More author details
Toc

Table of Contents (17) Chapters Close

Preface 1. Section 1: Introduction and Environment Setup FREE CHAPTER
2. Algorithmic Trading Fundamentals 3. Section 2: Trading Signal Generation and Strategies
4. Deciphering the Markets with Technical Analysis 5. Predicting the Markets with Basic Machine Learning 6. Section 3: Algorithmic Trading Strategies
7. Classical Trading Strategies Driven by Human Intuition 8. Sophisticated Algorithmic Strategies 9. Managing the Risk of Algorithmic Strategies 10. Section 4: Building a Trading System
11. Building a Trading System in Python 12. Connecting to Trading Exchanges 13. Creating a Backtester in Python 14. Section 5: Challenges in Algorithmic Trading
15. Adapting to Market Participants and Conditions 16. Other Books You May Enjoy

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...

lock icon The rest of the chapter is locked
Register for a free Packt account to unlock a world of extra content!
A free Packt account unlocks extra newsletters, articles, discounted offers, and much more. Start advancing your knowledge today.
Unlock this book and the full library FREE for 7 days
Get unlimited access to 7000+ expert-authored eBooks and videos courses covering every tech area you can think of
Renews at $19.99/month. Cancel anytime
Banner background image