Skip to Content
Hands-On Machine Learning for Algorithmic Trading
book

Hands-On Machine Learning for Algorithmic Trading

by Stefan Jansen
December 2018
Beginner to intermediate
684 pages
21h 9m
English
Packt Publishing
Content preview from Hands-On Machine Learning for Algorithmic Trading

Combining factors from diverse data sources

The Quantopian research environment is tailored to the rapid testing of predictive alpha factors. The process is very similar because it builds on zipline, but offers much richer access to data sources. The following code sample illustrates how to compute alpha factors not only from market data as previously but also from fundamental and alternative data. See the Notebook multiple_factors_quantopian_research.ipynb for details.

Quantopian provides several hundred MorningStar fundamental variables for free and also includes stocktwits signals as an example of an alternative data source. There are also custom universe definitions such as QTradableStocksUS that applies several filters to limit the backtest ...

Become an O’Reilly member and get unlimited access to this title plus top books and audiobooks from O’Reilly and nearly 200 top publishers, thousands of courses curated by job role, 150+ live events each month,
and much more.
Start your free trial

You might also like

Machine Learning for Algorithmic Trading - Second Edition

Machine Learning for Algorithmic Trading - Second Edition

Stefan Jansen

Publisher Resources

ISBN: 9781789346411Supplemental Content