Title: Trading Evolved – Anyone can build killer trading strategies in Python
Author: Andreas F. Clenow
Accompanying Website: https://www.followingthetrend.com/trading-evolved/
Purchased from Amazon Spain on 18 Oct 2020 for EUR 37,88.
What the book is about:
The book sets out to explain in technical depth how to install and use the Python programming language open source Zipline backtesting library. Backtesting is the designing and testing of trading strategies using historic time-series data. Python and all the necessary Python libraries are run in Anaconda (Jupyter Notebook to be specific, an app within Anaconda) which is a very convenient environment for working with Python. Some general padding on investment and trading topics, and the Python language itself, is also provided in the book. The Zipline library was developed by a company called Quantopian. It is important to note that Quantopian recently shut down its business. However, from looking at the online chatter on the relevant forums it would seem there may be an active support group for Zipline. Hence it is possible that the Zipline library may continue to be available, but BE WARNED such events don’t bode well for the whole thing being anywhere close to a smooth hassle-free experience, or even broadly functional at all. In fact quite the opposite, as explained further below.
I wanted something practical and interesting in the Python programming language space to follow on from the Udemy course ‘2020 Complete Python Bootcamp From Zero to Hero in Python’ which I completed in November 2020. While the book emphasises trading, I felt it was worth seeing if any of the backtesting concepts put forward could be applied to the conservative investing space, which would be more my style. The overall idea was to see how the Python programming skills I had accumulated measured up in terms of being able to implement the backtesting methodologies using Python that were advocated by the author.
Content and Style:
For details it’s best to go to Amazon and take a detailed look at the book contents there. I am up to almost the end of Chapter 7, Backtesting Trading Strategies, from the total of twenty-five chapters. I can’t go any further until I’ve resolved the Anaconda kernel errors when I open Jupyter Notebook with the Zip35 environment running. There are so many unanswered queries about errors on the various support channels that I’d imagine it’s going to be up to myself to solve this and no doubt other errors encountered. But there is a lot to be learned by trying to do this.
Does it keep its promises?
My opinion is a definite ‘no’. I would award the book 2/10 from this viewpoint.
This is a challenging, fascinating and interesting subject area so I will keep building Python skills and attempting to find solutions to the issues encountered here. I will update this review with anything interesting and useful discovered.