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The Best Books for Learning Quantitative Finance

Learn foundational quant concepts and skills to land your next quant job.


So you’re looking for some good book recommendations to add to your quantitative finance reading list. Well, you’re in the right place. In this article, we’ll cover a handful of helpful books that cover foundational concepts within the field of quantitative finance. While this won’t cover the entire remit of information that you may need for a quant job, we will share some tried and tested resources that will aid you along your journey.

The quantitative finance books that we’ll cover in this article will span two broad areas:

  1. Machine Learning / Algo Trading: the process of developing computational trading strategies that are underpinned by machine learning or other algorithms.

  2. Derivatives and Volatility Trading: learn about the types of financial derivatives that exist and what fundamental strategies exist to trade them.

Machine Learning & Algo Trading Books

Machine Learning for Algorithmic Trading

If you are an aspiring quant who is new to Python and algorithmic trading, this would be the perfect book for you. In this book, Jansen covers the following:

  • How to design supervised, unsupervised, and reinforcement learning algorithms for trading strategies using Python. You’ll also pick up and learn many popular python libraries such as scikit-learn, Tensorflow, and backtrader.
  • How to process, clean, and manipulate market, fundamental, alternative, and financial news data to then apply to trading strategies.
  • How to use advanced natural language processing and deep learning strategies to develop tradeable signals.

Overall this book is great if you’re interested in a resource that emphasizes the application of algorithmic trading over deep theoretical background information and advanced mathematical formulas. Furthermore, a lot of the Python skills that you’ll learn in this book will serve you well in a quantitative finance job. The next book we discuss, however, will cover more of the theoretical background behind each machine-learning algorithm.

Introduction to Statistical Learning / Elements of Statistical Learning

Introduction to Statistical Learning (ISLR) and Elements of Statistical Learning (EOSL) are both great books for learning foundational concepts in statistics and machine learning. While ISLR tends to be geared more towards undergraduates with some background in elementary statistics, EOSL is more advanced and dives deeper into the mathematics underpinning many machine learning models. Here’s a glimpse of what you can expect to learn in the EOSL book

  • Linear regression along with how it can be improved through the use of variable selection techniques and penalty/shrinkage methods.
  • Details on the construction of more advanced models such as Random Forests, Neural Networks, and Graph-based models.
  • An overview of parametric and nonparametric supervised/unsupervised learning methods as well as their advantages and disadvantages in relation to the bias-variance tradeoff.

The concepts covered in both of these books often pop up in quantitative finance interviews, so using this book as a study guide can be very helpful. Furthermore, both of these books have practical implementations in R which will help you ensure that you can actually implement the different concepts that you’ve learned.

Derivatives & Volatility Trading Books

Options, Futures, and Other Derivatives

“Options, Futures, and Other Derivatives” is often viewed as the bible to many professionals within the field of quantitative finance. Note that this book is very extensive, and going through all of this material will definitely take a significant amount of time. Nonetheless, Hull covers many foundational finance concepts in this book that are must-knows if you would like to get a quant job. Here are a few concepts that you can expect to learn:

  • Learn the fundamentals of what is a future contract, what is an option, who are hedgers, and who are arbitrageurs.
  • Understand what strategies exist for hedging futures and what strategies exist for trading and pricing options.
  • Gain an understanding of the many different types of derivatives such as credit derivatives, interest rate derivatives, energy derivatives, and commodity derivatives.

Overall this quantitative finance book has an abundance of knowledge covering many fundamental financial concepts and their application to quantitative finance. You can use this book as a reference to find concepts that you may not remember or are interested in learning more about.

Option Volatility and Pricing: Advanced Trading Strategies and Techniques

This book may be one of the most accessible quantitative finance books about options that is currently available. In this book, Natenberg takes you from the basics of what options are to advanced strategies for trading them. You'll learn:

  • The foundations of options theory, dynamic hedging, and volatility trading strategies.
  • How to think about risk analysis and managing any position.

The great part about this book is that it hides away many of the advanced mathematical formulas that are flooded in other financial texts. In doing so, it provides just the right amount of detail to understand many of the underlying concepts and leaves the reader with the opportunity to dive deeper into the areas they so choose.

Dynamic Hedging

Dynamic Hedging is one of Nassim Nicholas Taleb’s more popular books. Taleb is a mathematical statistician and former options trader who has written many popular books such as “Skin in the Game” and “Antifragile”. In Dynamic Hedging, Taleb covers options hedging and arbitrage from the perspective of professional traders and money managers. Here are some concepts you can expect to learn from this book:

  • Learn about markets, instruments, and people that make up the financial ecosystem.
  • Learn how to measure option risks with Black-Scholes and other techniques.
  • Learn how to measure option risks as well as how to trade and hedge exotic options.

Overall, this book is filled with useful content but isn’t as dense as “Options, Futures, and Other Derivatives”. Also, if you already enjoy Taleb’s work you’ll likely find this book to be a fun read.

Final Note

Thanks for reading this article. We hope these books and resources on quantitative finance concepts will come in handy throughout your journey as a quant. If you enjoyed it, feel free to check out more of our content on our quant blog. Also, if you’re looking for openings in quantitative finance check out OpenQuant for the best quant jobs.