I really enjoyed reading Algorithmic Trading: A Practitioner’s Guide by Jeffrey M. Bacidore. Before starting, I imagined it would cover various strategies for trading in the markets, along the lines of “buy on this condition, sell on this condition”. But that is not what this book covers. What trade to make is always a given, typically from a portfolio manager. Instead, the book is all about how to make it happen, almost always by portioning out the trade little by little, while trying to get the best price.
It is fascinating how many factors come into play when implementing this seemingly simple task. The book covers all parts of this process in a clear and concise way, with lots of illuminating examples. The author has over 20 years of experience in the field of algorithmic trading, both from industry and academia. I particularly liked all the examples of implementation corner cases and gotchas that clearly come from experience.

On Comments in Code
I used to think that I didn’t need comments if I wrote self-documenting code. However, I have realized that I do write comments, and that I find them really useful. To see how many comments I write, and what kind they are, I wrote a script to analyze my git commits from the last six years. In total, seven percent of my committed lines contained a comment. This blog post has details on what constitutes good and bad comments, as well as more statistics from my script.
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