The top 5 essential books about algorithmic trading every beginner should start with (2024)

Diyan Doychev - May 18, 2020

In this post, you are going to find a list of the top 5 essential books that you should start with if you are interested in algorithmic trading.

We do not need to tell you that algorithmic trading a huge topic to cover. If you already did a search, for sure you have discovered that there are hundreds, if not thousands of books and websites on the subject. While this abundance of knowledge is great, it is also making it hard to decide where to start. A lot of the sources are quite academic and can be difficult to grasp without any prior knowledge in mathematics and statistics. It can be quite discouraging for a novice algorithmic trader if he stumbles upon such a book at the beginning of his path to learning.

Fortunately, there are some excellent books about quantitative and algorithmic trading that are suited for beginners. Here are the top 5 that will help you gradually get comfortable with the topic:

Contents hide

1 Quantitative Trading: How to Build Your Own Algorithmic Trading Business, by Ernest P. Chan

2 Building Winning Algorithmic Trading Systems. A Trader’s Journey from Data Mining to Monte Carlo Simulation to Live Trading, by Kevin J. Davey

3 Trading Systems: A New Approach to System Development and Portfolio Optimisation, by Emilio Tomasini

4 Trading Systems and Methods, by Perry J. Kaufman

5 Evidence-Based Technical Analysis: Applying the Scientific Method and Statistical Inference to Trading Signals, by David Aronson

Quantitative Trading: How to Build Your Own Algorithmic Trading Business, by Ernest P. Chan

In this book, Dr. Chan describes how an individual trader can set up a profitable small-scale quantitative trading business, thanks to the lack of restrictions that institutional traders in funds face. It is a good introduction and practical guideline for algorithmic trading for beginners who are just starting out. Most of the books on the topic of algorithmic trading are quite academic, abstract, and distant from the average retail trader. Dr. Chan takes a different path and explains the matter with a “hands-on” approach, in a way that it can be easily understood by anyone. The book touches base on all the important topics such as:

  • Where to seek trading ideas inspiration?
  • What is backtesting and how to use it to evaluate trading systems?
  • How to apply proper risk management?
  • How to build an algorithmic trading system – semi or fully automated?
  • Gives a couple of example trading strategies (momentum and mean reversion)
  • It includes examples in popular programs like MatLab and Excel.

If you are at the beginning of your journey as an algorithmic trader, this book is a good place to start. The reader who has some understanding of the basics of automated trading might be disappointed though, as the book barely scratches the surface of some of the topics. However, this seems to be on purpose, as adding too many details would make the book too complex for beginners.

Building Winning Algorithmic Trading Systems. A Trader’s Journey from Data Mining to Monte Carlo Simulation to Live Trading, by Kevin J. Davey

Mr. Davey took an interesting approach in his popular book “Building Winning Algorithmic Trading Systems. A Trader’s Journey from Data Mining to Monte Carlo Simulation to Live Trading”. He covers all the important topics any future algorithmic trader should cover in a story-like narrative around his personal experience:

  • How to test and evaluate a trading system?
  • Historical backtesting
  • Out-of-sample testing
  • Walk-forward analysis
  • Real-time analysis
  • Monte Carlo analysis
  • Position sizing and money management

The story-like approach made the book very easy to read so quite a lot of people choose it as their first introduction to algorithmic trading. In addition, Davey shares important tips you should consider before you take the plunge and transition to full-time trading:

  • How much trading capital do you need to start algorithmic trading full time?
  • Why you should not forget to consider your living expenses?
  • How to set up your home trading office?
  • Why is it important to have support and understanding from your family, before starting to trade full time?
  • How many trading strategies you should have before you are ready to start trading full time?
  • How to find good brokers and open trading accounts?
The top 5 essential books about algorithmic trading every beginner should start with (1)

Trading Systems: A New Approach to System Development and Portfolio Optimisation, by Emilio Tomasini

“Trading Systems: A New Approach to System Development and Portfolio Optimisation” is a great book for everyone looking for a methodical way to design and test algorithmic trading systems that can be adjusted to work on every market. The book is divided into three parts. In the first part, you will find a short practical guide on how to develop and evaluate trading systems and a theoretical basis you need for algorithmic trading. The second part covers a few practical applications of trading systems. In part three you can learn how to put together systems for different markets.

The book overviews the steps for:

  • How to design technical trading systems?
  • What are the elements of an algorithmic trading system?
  • How to test trading systems properly with in and out of sample data?
  • What are the methods for evaluating a trading system’s predictive power?
  • Which metrics to use that can compare against other systems?
  • What is periodic re-optimization?
  • How to construct a dynamic trading systems portfolio?

Trading Systems and Methods, by Perry J. Kaufman

“Trading Systems and Methods” is one of the books considered as pillars of knowledge in systematic and algorithmic trading. The first edition is published in 1998, but there are several recent revisions. It is quite extensive, spanning over 1200 pages. The book starts with the basic concepts and makes an introduction to the necessary math and statistics needed for further topics. The book gives a lot of detailed information on:

  • technical indicators
  • trading systems
  • systematic methods
  • trend following, momentum, mean-reversal and arbitrage trading systems
  • risk management and many more.

“Trading Systems and Methods” could be too overwhelming for some beginners, because of the vast amount of information covered. However, it will be appreciated by traders who want to dig deeper into the details of systematic trading. You can read it through chapter by chapter and gradually build your knowledge. Later on, you can also use it as a reference and jump quickly to the topics you need, because it is structured very well.

Evidence-Based Technical Analysis: Applying the Scientific Method and Statistical Inference to Trading Signals, by David Aronson

David Aronson’s “Evidence Based Technical Analysis” (“EBTA”) is another book that should be in your reading list if you want to develop as an algorithmic or quantitative trader. There is a level of skepticism surrounding some of the methods deployed by the practitioners who are using technical analysis. This is mostly due to the mainstream use of overly vague terminology and methods claiming to have predicting power. Thousands of novice traders and investors have been lured to apply these simplified methods into their trading. As a result, many end up losing money in the process. The author’s point is that those who take a casual approach towards technical analysis for sure would get casual results. The reality is that finding and trading a profitable system (as anything else in life) requires a lot of learning, hard work, and dedication.

Aronson takes a scientific approach towards evaluating the methods of technical analysis as a valid source of profitable trading signals. In the book he takes the reader on a long and very detailed journey through a lot of different theories and topics, aiming to show a different perspective on why technical analysis would or would not hold any predictive power:

  • What is the difference between objective and subjective technical analysis?
  • What are the most common biases and how do they affect the quality of technical analysis methods?
  • Basics of statistical analysis
  • Probability experiments and random variables
  • Hypothesis tests and confidence intervals
  • Solutions for dealing with data-mining bias
  • Challenging the efficient markets hypothesis and random walk
  • Behavioral finance as a theory of nonrandom price motion
  • Nonrandom price motion in the context of efficient markets
  • Conclusions and case studies on the future of technical analysis

“Evidence Based Technical Analysis” (“EBTA”) is not the first choice for many people, as in some aspects it is not an easy read. This is because the author covers a wide variety of theories in order to give a detailed overview of the topic from different angles. As a result, quite frequently the narrative drifts away from the main topic. On the other hand, every piece of information is included for a purpose, with the aim to help you build the mindset needed to succeed in systematic trading.

We hope that this short list of books about algorithmic trading was useful for you! Don’t forget to check out our series of educational articles on quantitative finance and systematic trading or sign up for our newsletter for additional great content!

This article is a part of a series on quantitative finance developed by “Quantitative Strategies Academy” Foundation according to its mission for the benefit of people who want to know more about quantitative analysis and automated systems.

Disclaimer: This is an educational website operated and maintained by “Quantitative Strategies Academy” Foundation. No part of the content of this website constitutes a recommendation to apply any investment strategies presented or implied in any of the site content. No part of this website or its content should be considered any type of investment or other advice related to your personal circumstances. You must take independent financial advice from a qualified professional when making any type of financial decision which may or may not be directly related to information found on this website.

As someone deeply entrenched in the field of algorithmic trading, I can affirm the significance of a well-curated reading list for anyone entering this complex domain. The article by Diyan Doychev delves into the realm of algorithmic trading, providing an insightful compilation of top books tailored for beginners. Let's break down the key concepts discussed in each book:

  1. Quantitative Trading: How to Build Your Own Algorithmic Trading Business, by Ernest P. Chan:

    • Focus: Dr. Chan offers practical insights on setting up a profitable quantitative trading business.
    • Key Topics Covered:
      • Inspiration for trading ideas
      • Backtesting and its evaluation
      • Risk management
      • Building algorithmic trading systems (semi or fully automated)
      • Example trading strategies (momentum and mean reversion)
      • Examples using popular programs like MatLab and Excel
  2. Building Winning Algorithmic Trading Systems, by Kevin J. Davey:

    • Approach: Davey adopts a narrative approach, sharing his personal journey as an algorithmic trader.
    • Highlighted Areas:
      • Testing and evaluating trading systems
      • Historical backtesting
      • Out-of-sample testing
      • Walk-forward analysis
      • Real-time analysis
      • Monte Carlo analysis
      • Position sizing and money management
      • Practical tips for transitioning to full-time trading
  3. Trading Systems: A New Approach to System Development and Portfolio Optimisation, by Emilio Tomasini:

    • Structure: The book is divided into three parts, offering a methodical approach to designing and testing algorithmic trading systems.
    • Key Insights:
      • Designing technical trading systems
      • Elements of an algorithmic trading system
      • Testing systems with in and out of sample data
      • Evaluating a trading system's predictive power
      • Metrics for system comparison
      • Periodic re-optimization
      • Constructing dynamic trading systems portfolios
  4. Trading Systems and Methods, by Perry J. Kaufman:

    • Pillar of Knowledge: Considered foundational in systematic and algorithmic trading, this extensive book covers various aspects.
    • Encompassing Topics:
      • Technical indicators
      • Trading systems
      • Systematic methods
      • Trend following, momentum, mean-reversal, and arbitrage trading systems
      • Risk management
  5. Evidence-Based Technical Analysis: Applying the Scientific Method and Statistical Inference to Trading Signals, by David Aronson:

    • Scientific Approach: Aronson adopts a scientific perspective to evaluate the methods of technical analysis.
    • Exploration Includes:
      • Objective vs. subjective technical analysis
      • Common biases affecting technical analysis
      • Basics of statistical analysis
      • Probability experiments and random variables
      • Hypothesis tests and confidence intervals
      • Dealing with data-mining bias
      • Challenging the efficient markets hypothesis
      • Behavioral finance in the context of nonrandom price motion

Each of these books contributes uniquely to the understanding of algorithmic trading, covering essential concepts from practical implementation to theoretical foundations. Whether you're a novice or have some experience, this curated list provides a comprehensive starting point for navigating the vast landscape of algorithmic trading.

The top 5 essential books about algorithmic trading every beginner should start with (2024)
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