Great. As a quantitative developer, I have several friends that work as quantitative traders at placed like IMC, Jump Trading, DRW, and Citadel (with some other ex-quantitative traders now working at hedge funds like Balyasny, Point 72, and more). In fact, I've even mentored a quantitative trader looking to polish up his interview skills before gunning for a more senior role at another firm. Why am I mentioning all this? Well, because during my time speaking to other quantitative traders, I've been able to come up with a list of 5 books that every prospective quantitative trader should read if they'd like to break into the industry. Some of these books I've read myself, others have been strongly recommended to me by other quantitative traders.
Great question. This article is a revised version of that video. Since the aforementioned video, I've removed certain books and added new books that I believe are more critical for one's success in breaking into quantitative trading. So, let's start.
Ah, but before we do, note that as a caption to each image below I included a link to the book so you won't need to go and search for it yourself.
Consider this your holy bible.
Yes, it is that important.
Every quantitative trading intern has a copy of this book on their desk. I've read this book myself and can personally vouch for it (albeit, I don't use the knowledge contained in this book nearly as frequently as a trader does, so some of it has been lost over the years).
This is not one of them. Sheldon starts with the basics, building on what you've learned through every chapter, and asking and answering questions he knows you're thinking about. The charts and figures he uses compliment his content which, above all else, is the largest selling point of his book. Sheldon is an industry veteran, and the breadth and depth of his knowledge are imbued in every page of this book.
I'd like to take a second to give an honorable mention to Nassim Taleb's Dynamic Hedging: Managing Vanilla and Exotic Options.
Many quantitative traders I've spoken to have compared Nassim's book to being just as important as Sheldon's. These two books cover the exact same topics, so feel free to pick one or the other (but not both, not unless you have a lot of free time on your hands).
That's right. You don't need to learn to code to become a quantitative trader. But wouldn't it be nice if you knew how to code, and other candidates competing for the same role didn't? Yeah, that would be nice.
It's no surprise that the world of quantitative trading is becoming more-so data-driven now than it ever has. That doesn't mean that traders are going anywhere anytime soon; however, what it does mean is that traders will need to stay up-to-date with techniques to extract, transform, interpret, and make decisions regarding data. This book helps you do just that. Wes McKinney is a legend in the Python space. He isn't only a (former) quantitative developer, but an active member of the Python community, having being one of the founding writers of the Pandas library.
I've also read this book, and can personally vouch for it (albeit, I don't write in Python at work, so much of it has also been lost on me). It won't only help you become a standout quantitative trader, but will also help you learn the language of quantitative developers (another major selling point).
If Sheldon Natenberg's Option Volatility & Pricing is your bible, consider this your pocket bible.
I like to read Frequently Asked Questions in Quantitative Finance as a refresher anytime there's a concept I run into that I'm unsure of. This book is over 500 pages, and I haven't read it back-to-front; but, that's not how this book is supposed to be read. It includes both short-form and long-form explanations on key models, important formulae, popular contracts, essays and opinions, a history of quantitative finance, sundry lists, the common mistakes in quantitative finance, and more.
For example, this book has sections on how to dress for an interview, frequently asked interview questions, popular quantitative trading books, etcetera. Though, one of this book's key selling points for me was the image of Paul stepping on a communist flag on the cover.
Yes, math. And you'll need to be good at it too. Otherwise, it'll be difficult to qualify as a quantitative trader. Now that doesn't mean that you'll need to solve the Riemann hypothesis, but you will need to have a strong proficiency in math to be considered for the position.
Whether the test takes place at the beginning of your interview journey with said company (as a technical screen), or in the final round of your interview on a whiteboard in front of three interviewers, you can guarantee that it'll be tested. Knowing this, you might as well arm yourself with the concepts that are most likely to be tested by picking up a copy of Introduction to Linear Algebra. I have not personally read this book, but that doesn't mean it's any less important than the books mentioned prior. This is a book that was recommended to me by a veteran quantitative trader (and ex-quantitative researcher) at Jump Trading, so I'm sure it'll come in handy.
Yes, even more math. If you're frowning, maybe quantitative trading isn't right for you. But if you're smiling, then you're reading the right article. As someone who doesn't come from a math background - I took two statistics courses in university - I was looking for a book to brush up on statistics that isn't riddled with convoluted formulae. What immediately attracted me to this book is that it was written by an English major (that now works as a data scientist), and so I thought to myself that it couldn't be that bad.
I read this book from end-to-end, and I can say with confidence that it is written in an incredibly easy to understand way. It includes questions at the end of each chapter, and actually includes the answers to those questions at the end of the book. It goes over concepts that day traders clamor about, but no nothing of, including probability, uncertainty, binomial distribution, beta distribution, conditional probability, Bayes' theorem, parameter estimation, the normal distribution, probability density, cumulative distribution, quantiles, hypothesis testing, posterior odds, and more. The interesting thing about this book is that it starts off by not talking about any of this. It starts by putting you in the mindset of someone who thinks in terms of numbers and lays a strong statistical foundation for you to build on.
Hopefully by now you have a better understanding of the books you need to read if you're to become a quantitative trader. These five books are a collection of books that I've both personally read, and have been recommended by veterans in the space. If you get through all five books, that's impressive; but, not everyone has time to read all these five books within the window they'd like to start applying to quantitative trading firms. If I was to recommend an order in which you read these books, I'd recommend Book 1, Book 2, Book 5, Book 4, and Book 3. Since Book 3 is a reference-like book, you can sprinkle some of its reading into the mix starting after Book 1.
I hope this helped. Good luck on your quantitative trading journey!