Resources

Machine Learning for Algorithmic Trading - Stefan Jansen

level: intermediate

This book explains how different machine learning techniques can be applied to algo-trading. It doesn’t focus on a single technique like deep learning, but touches many different techniques instead. For example, it has some good content on Bayesian machine learning.

Because of all the different techniques described, this book is over 800 pages long. If you want to start using machine learning in your strategies, this book is a must-have in my honest opinion. One thing to keep in mind is that because machine learning is progressing so fast, some libraries and examples mentioned are outdated.

Advances in Financial Machine Learning - Marcos Lopez de Prado

level: intermediate

This book has several innovative and fresh ideas about approaches to algo-trading. For example using volume-based candlesticks rather than time-based candlesticks.

And although the included code snippets are written in Python, the underlying theory is applicable to any implementation. Also, this book contains great information about how easy it is for your approach to developing look-ahead bias without realizing it.

Marcos Lopez de Prado also has some good YouTube videos where he explains much of the same theory. So check those out first if you are not sure yet about buying this book. Also, the book felt a bit fragmented at times, and the videos help to make the topics covered in the book more coherent.

Trading Systems - Emilio Tomasini

level: beginner

A good book for a beginner that has plenty of pragmatic tips how to build, test, optimise and implement robustness trading systems. There is some AmiBroker code included, but even without understanding this, you can still follow along.

After explaining the basic theory behind developing algo-trading strategies, the book includes a step-by-step example. There are also many colorful charts included, so be aware if you order the e-book version and want to view it on a gray-scale e-reader.

Lastly, if you are new to statistics, this book also has a good introduction on how to deal with forecasts in the context of uncertainty.

Automated Stock Trading Systems - Laurens Bensdorp

level: beginner

Easy to understand and follow with extra attention on how to diversify your portfolio using different strategies. The book also describes 7 concrete strategies and the rules that need to be implemented for each of these strategies. The strategies are easy to understand and are a mix of trend-following and mean-reversion. The book doesn’t contain any code snippets.

Not sure about the merits of the strategies described in this book, since the evaluation criteria included are too simplistic in my opinion. But I would argue implementing some strategies yourself from scratch is a great learning experience.

Like many other "Amazon printed" books, the images are not great. But in this case, fortunately, they are not that important to understand the content.

Systematic Trading - Robert Carver

level: intermediate

Robert Carver is a regular guest at the podcast Top Traders Unplugged and has written several good books, of which this is one.

He develops his own algo-trading software (available under open-source) and that shows. There are enough details in the book to actual implement the strategies in your own code. If anything, due to the high density of information, some chapters require multiple reads before grasping everything.

Algorithmic Trading - Ernest P. Chan

level: intermediate

This book does not try to sell you trading strategies, but teaches you the methods and underlying discipline to achieve good strategies.

The code snippets included are written in MATLAB. But don’t let that put you off, they are easy to understand, especially if you have some background in math or another computer language. The chapters are divided between mean-reversion and momentum strategies and the last chapter has useful tips on how to approach risk management.

This book is more theoretical than some other intermediate books on this list. But that is also a major bonus; it means it will stay relevant longer, and not be outdated as quick as books that focus more on programming using third-party libraries.

Applied Time Series Econometrics - Helmut Lütkepohl

level: advanced

This book provides a great foundation for understanding much of the theory behind time series analysis. It clearly explains commonly used models and important concepts like stationary and non-stationary processes. It requires good knowledge of math at least at an undergraduate level.

The examples used in this book cover both macro-economical and investment oriented use-cases. So this is in particular a great book if you want to strengthen your overall knowledge of (non-stationary) timeseries.

Besides the content, there is also an accompanying Java project hosted at http://jmulti.de that implements various models described in the book, like an ARIMA model. This Java project is a bit outdated since the code-base pre-dates 2010, but nonetheless a nice bonus.

151 Trading Strategies - Zura Kakushadze and Juan Andrés Serur

level: intermediate

This book provides an overview of many strategies, divided by asset class. So there are strategies for options, stocks, bonds, etc. Each strategy is described shortly, using simple mathematical formulas and often a reference to the original publication. If you have only been exposed to a limited set of strategies, this will help to broaden your horizon and get new ideas.

Although the formulas are concise, essential information is sometimes missing to be able to transfer these strategies into code. For example, the description of a mean-reversion strategy doesn’t explain how to find correlated assets, just how to generate a signal given that they are correlated.

Some chapters, like real estate strategies, have so little own content that they could have better left out in my opinion. At best, these chapters are useful as a reference to other publications, but I’m not sure that justifies putting them in this book.

Also, note there is no analysis included about the performance of the strategies. So expect to do a fair amount of research before the described strategies are ready for a back test.

The Evaluation and Optimization of Trading Strategies - Robert Pardo

level: beginner

If you are new to algo-trading and need insights on how to develop a trading strategy and test and optimize it, this is the book for you. It covers most topics important to algo-traders and the content is easy to grasp and explained in plain English with many examples.

Even if you don’t have a background in software development or math, you can easily follow along. And although the book is more than 15 years old, most of it is still applicable today. Of course, the downside of not using code or math to explain the concepts, is that it is a bit less concise. But that is to be expected.

If there is one small complaint, there are a lot of white spaces, tables and charts that not add much. So this 360+ pages book could have easily been condensed to 200 pages.

Quantitative Trading - Xin Guo and others

level: advanced

This book combines academic research with industry trends. It covers a wide range of topics, from statistical trading models to optimizing order execution and risk management. Sometimes it feels a bit like each author focused on their own area of expertise, leading to somewhat disjointed chapters. Still, the content is unique and the authors are clearly experts.

Because of the wide range of topics, some chapters lack the details to directly apply them to your own strategies. So it serves better as a source of inspiration, rather than a pragmatic approach to algo trading. Please note you’ll need a firm grasp on math to get most out of this book.

Some of the content is more catered towards trading firms than retail traders. For example, optimizing trade execution is most applicable when you place large orders that would otherwise suffer from a lot of slippages.

Better System Trader

One of my favourite podcasts about systematic trading. Every episode has a different trader as guest. The focus is on pragmatic topics that can be put directly to work in your own strategies.

Since there is often accompanying visual content, you might want to watch the episodes on their YouTube channel instead.

Chat with Traders

This podcast contains several episodes and interviews with professional algo traders. Especially the coverage of potential pitfalls of going live with fully automated trading systems might prove to be extra helpful and insightful.

Here you can find which episodes contain algo-trading topics.

Top Traders Unplugged

All about rule based investment in the context of trend following strategies. There are some very experienced traders on this show, and they share a lot of useful tips and best practices.

The episodes with Rob Carver as guest are particularly interesting since he is a retail algo-trader himself (but not yet using roboquant ;). An additional benefit for algo-traders is that most trend following strategies are not that difficult to translate into executable code.

One thing to keep in mind is that most presenters come from a CTA (Commodity Trading Advisor) background, and as a result many of the covered assets are commodities and futures, and not individual stocks.

Patrick Boyle on Finance

Provides good background information on trending financial topics. Besides providing excellent insights into these hot topics, I really enjoy the way it is presented with a good amount of dry English humor.

For example checkout this episode: The Bitcoin Green Revolution - Is Cathie Wood Right About Bitcoin?

Flirting with Models

Explore systematic investment strategies, ranging from value to momentum and merger arbitrage to managed futures. The nice thing about this podcast is that there are many types of guests interviewed, ranging from traditional fund managers to retail crypto traders.

Roots Report

Discusses recent developments in the financial market on a weekly basis. If you don’t have the time to stay up to date with the latest financial news, this is an easy way to catch-up.

The Quant/Financial Engineering

Discusses the latest trends in data analytics, asset management, blockchain and risk management. If you are interested in the application of machine learning, definitely listen to this podcast.

Confessions of a Market Maker

Shares educational trading experience, coupled with some entertaining stories. Not that much focus on trading automation, but good content on trading in different asset classes with knowledgeable guests.