Successful Algorithmic Trading (2024)

To the point. The author sheds light on alot of pitfalls as well as best practices. The initial chapters lay foundation to the field with succinct summaries on the tenets of quantitative finance. Later, with the help of code examples the author builds an end to end backtesting engine and runs a few alpha strategies to show how it would look like.

This book will also help build newcomers confidence that it can be done with the amount of code and due diligence needed to take it off the ground. It is much better than E.Chan's books as it gives all code in python as well as where to source your data from.

Also this is my third book after reading Narang's HFT and Chan's Algo business books and by far this is the most pragmatic of all.

Cover variety of important topics of algorithmic trading. The good thing is that the book provides python code and readers can easily try and test the ideas.

Focused on beginners.

I've used this book to help plan out requirements using it's own heading names. Very well organized. As is almost always the case, the python code is outdated. You will have to research what the modules have been replaced with before testing the suggested python code