Book Image

Machine Learning for Algorithmic Trading Bots with Python [Video]

By : Mustafa Qamar-ud-Din
1.5 (2)
Book Image

Machine Learning for Algorithmic Trading Bots with Python [Video]

1.5 (2)
By: Mustafa Qamar-ud-Din

Overview of this book

Have you ever wondered how the Stock Market, Forex, Cryptocurrency and Online Trading works? Have you ever wanted to become a rich trader having your computers work and make money for you while you’re away for a trip in the Maldives? Ever wanted to land a decent job in a brokerage, bank, or any other prestigious financial institution?We have compiled this course for you in order to seize your moment and land your dream job in financial sector. This course covers the advances in the techniques developed for algorithmic trading and financial analysis based on the recent breakthroughs in machine learning. We leverage the classic techniques widely used and applied by financial data scientists to equip you with the necessary concepts and modern tools to reach a common ground with financial professionals and conquer your next interview.By the end of the course, you will gain a solid understanding of financial terminology and methodology and a hands-on experience in designing and building financial machine learning models. You will be able to evaluate and validate different algorithmic trading strategies. We have a dedicated section to backtesting which is the holy grail of algorithmic trading and is an essential key to successful deployment of reliable algorithms. The code bundle for this video course is available at - https://github.com/PacktPublishing/Machine-Learning-for-Algorithmic-Trading-Bots-with-Python
Table of Contents (6 chapters)
Chapter 5
Build Advanced Trading Algorithm
Content Locked
Section 2
Implement Scalpers Trading Strategy
In this video, you shall implement scalp trading with two indicator signals and bollinger bands. - Implement scalp trading class - Import BitCoin and Ethereum securities custom dataset into Zipline - Run Backtest session for scalp trading with custom dataset