Algorithmic Trading: A Practitioner's Guide

This book is a quick read and a great high-level introduction to the world of algorithmic trading. The author covers order types, venue types, trading algorithms, order routers, and trading performance evaluation. The resources at the end of the book provide the reader with plenty of material should they want to learn more. This book is the perfect introduction for early career traders as well as analysts and PMs or people in leadership roles that need to understand how to evaluate and improve trading performance.

Great book for getting a more robust POV of how algorithmic trading strategies works at hedge funds, banks, etc. Not a typical algorithmic trading book that talks about specific trading strategies or backtests

Most of the "algo*** trading" books will be either too theoretical, like Jaimungal's book, full of SPDEs and Lagrangians/Hamiltonians which is almost of no use in practice; or too "fragmented" like a collection of disconnected practical facts and heuristics supplemented with college level statistics and time series (ARMA/GARCH j*nk) with no use in practice again, from the other end. Jeff's book is quite unique and nonsense-free, with a fair balance and deep thoughts of many hard topics in algorithmic trading, of coz, of great practical uses. This will be simply the best book on this topic.

As a former algorithmic trader at a major hedge fund and at a major institutional broker, I wish I had this book when I was starting out. This book provides the perfect level of detail on how trading algorithms actually work in practice, how they should be used, and how to evaluate performance, but without getting bogged down in the finer details that are only relevant to algo developers and quants. A must read for portfolio managers and traders alike.

If one wants to learn about what algo trading practitioners are really doing, how they do things and what are their main considerations, Jeff's book is a really nice resource. It contains basically all the main aspects of a set of real algo trading strategies/system, and in depth discussion about the issues and the various solutions.

nice intro to algo trading

I really liked Jeff's book. Not only is it the best market microstructure book out there, the latter chapters constitute a great guide for data scientists to understand biases and design the proper experiments to evaluate execution performance.

The first few chapters are very nice and provide a great introduction to how markets work, and the reationale behind the (most basic) execution algorithms. The remaining half of the book looks like an effort to reach 200 pages, lacks cohesivenes, is redundant, and an overall waste of time.

Die Art und Weise wie das Buch strukturiert ist und die Informationen (hab nur kurz reingelesen) waren nicht überzeugend. Der Druck ist auch eher von schlechter Qualität. Mein Eindruck ist, das es einfach ein Buch ist mit dem schnell Geld verdient werden soll. Nicht zu empfehlen.

A couple of points 1. It covers everything from the basics, so this is perfect for beginners 2. On the flip side, the concepts are covered concisely which means it doesn't go into depth 3. Applicable regulation e.g. MiFiD RTS 6 is not covered much in the book.

First of all, I must say that I personally found this book very useful for me as a researcher at a hedge fund. It covers a lot of important topics people don't typically even mention in traditional quant courses. However, it must be said that the title is very much misleading. "Algorithmic Trading" is a wide topic and here only one very narrow aspect of it (which isn't even that important for smaller traders) is covered. The whole book is exclusively dedicated to (large) order execution strategies. Unless you're planning to execute big orders which can potentially impact the market, then this book isn't really for you as vast majority of it is dedicated to working big orders over long time frames, routing orders to multiple venues including dark pools etc. Secondly, this isn't a "practitioner's guide" really, it is more of an overview. It was extremely useful for me to grasp some important ideas and pick up buzzwords for things I need to look up later, but it isn't something you just can quickly implement in practice. Now, "Efficient Order Execution: An Overview" isn't a very catchy title, but would fit much better. And if that was the title of the book, I'd give it 4 stars I reckon. Another problem I found is that towards the end it felt like the author was striving to reach a certain page count and some sections could have been summarized in literally one sentence instead of stretching them for 1-2 pages... I mean, some of this stuff felt embarrassing to go through. I.e., do you really need 2 pages to explain that sum of consecutive differences is the same as total difference or that negative edge would be what we call cost? Who is this book for - a sophisticated professional who will go code up dynamic programming optimization of his trade execution algo or a person who only has rudimentary understanding of basic math? Talking about basic math, towards the end there is quite a silly mistake which makes me a bit sceptical of author's competence in practical matters. The author says that in order to maintain the same mean when treating outliers, it's necessary do it in a symmetrical manner, i.e., 1% top and 1% bottom. This obviously is not only not always true, but something financial markets are notorious for - being very much skewed in one direction... So it might easily be the case that your 1% bottom outliers are huge and 1% top are barely above everything else, which obviously will affect the mean. In any case, I found the last chapter to be honestly all over the place and pretty much useless anyway... So, well, if you're looking for "Efficient Order Execution: An Overview", then I think it should be good... I have nothing to compare with though, so take with a grain of salt.

This is the best book that I’ve ever found on this subject

Great summary and refresher of everything I learned in my years at ITG analyzing algorithm performance. Wish I had this book from the beginning!