Posted on March 21, 2018, 2:56 p.m.
I feel GLORIOUS. After reading books about quantitative trading for nine years I feel like I finally found the right books. Perhaps they were there all along and I learned through other methods.
Edit 2018/4/6 updated praise for QEPM.
Do a search for books on Amazon with Quantitative Finance and you will get many fine books. However, most of them discuss pricing derivatives. I first read Paul Wilmot's "Paul Wilmott Introduces Quantitative Finance." I read the whole book cover to cover on a two week trip overseas. At 728 pages I think I would have been better off reading the first few chapters and looking for another book, not because there is anything wrong but the focus is entirely on pricing derivates. I feel that the reason for this was prior to 2008 "quant" (mostly) meant someone who built models to price derivatives. In the preface to "The Handbook of Equity Market Anomalies: Translating Market Inefficiencies into Effective Investment Strategies" Len Zacks explains: "In the aftermath of the global financial meltdown of 2008, the accuracy of the quant models of Collateralized Debt Obligations (CDOs) was called into question and many of the quants who created these models and worked for the major banks were downsized. At the same time, another type of quant model, the multifactor equity model, and it's creators were thriving.." Perhaps there are tons of people using exciting models to prices derivatives, it's just not my cup of tea. I am interested in multifactor models, and currently focusing on equities.
Here is the start of my list, as with all posts here is a work in progress. Some are more targeted at begginers and some are more academic. A final warning: I love books more than most people and have a garage full of them, however no book is a replacement for trying things on your own. The author of these books (this applies to academic research as well) have come to the conclusions under certain circumstances. Your circumstances may not be the same, so please find out for yourself what works and what doesn't. Books, blog posts, academic papers, etc. are good sources for ideas and starting points but shouldn't be taken as fact especially in a field as dynamic as trading.
- "Inside the Black Box: A Simple Guide to Quantitative and High Frequency Trading" by Rishi K. Narang I wish I would have read this book a long time ago, it would have saved me from reinventing the wheel. Things like risk model and execution model I built on my own without knowing what to call them. I certainly got the concepts for the risk model from elsewhere, however plugging them into a live trading strategy I had to do on my own, and it would have been easier having read his book. Chapters 3, 5 and 6 are worth the price of this book alone. I would recommend this to everyone interested in quantitative finance.
- "Quantitative Trading: How to Build Your Own Algorithmic Trading Business" by Ernie Chan Somewhere between an academic and a practical guide, I really like this book. Dr. Ernie has a PhD and his style is very academic, so this is a bit of an academic introduces how to build your own system at home. I would also recommend his other two books, they are somewhat sequels to this book with new strategies and benefits to working on your own. The code is all in Matlab, but is not hard to port to other languages.
- "Active Portfolio Management: A Quantitative Approach for Producing Superior Returns and Controlling Risk" by Grinold and Kahn. This is a very academic book, laying foundations for CAPM. This book is considered a classic, and will be on your shelf next to Shakespeare.
- "Building Winning Algorithmic Trading Systems" by Kevin J. Davey This book is 100% for beginners wanting to do systematic trading. On the homebrew to academic spectrum this book lands very close to the pure homebrew end. Kevin walks you through his journey from trading his own money and looking everywhere for help, sometimes from charlatans. He also has a good introduction to Monte Carlo methods. I think some of his strategies appear to be placing all of one's capital in a single instrument. All of his examples are in Excel and can be downloaded. I would read this book for a good introduction and then move on to more elaborate systems.
- "Following the Trend: Diversified Managed Futures Trading" by Andreas Clenow I love this book, it is a logical extension to Kevin Davey's book, where Clenow is showing you how to do trend following in a diversified systematic way. He also shows that if you adjust for risk, the historical returns of most managed futures funds are nearly identical. There is as much valuable information in this book on managed futures as other topics. He does not hold anything back and even spells out his motives for writing a book like this (advertisement). Clenow makes an argument that long equities are a horrible investment if you look at the risk/reward characteristics.
- "Hedge Fund Market Wizards" by Jack Schwager This book ranks pretty low on the heavy math scale, in fact I'm not sure if there is even one equation in it. However it is very useful to hear interviews with many successful hedge fund managers. Of course I thought the quantitate managers were the most interesting, and you can get some good ideas from discretionary traders as well. The risk/reward discussion in the Appendix is also very helpful and will make you question the use of Sharpe's ratio over other ratios (Sortino).
- "Quantitative Equity Portfolio Management" by Qian, Hua, and Sorensen This is the most academic book on this list, ironically the authors all seem to work in industry rather than academia at the time of publishing. However I think any technical person involved with long/short equity should get this book. As I stated at the start of this post there are tons of books on derivative pricing but few on long/short equity. This is the goto reference for quantitative equity strategies. When I started moving to larger amounts of capital I ran into a lot of problems and didn't have a lot of places to turn, this book was there. Chapters 2, 3, 8 were particularly helpful with risk and transaction costs. After I started reading this book I noticed terminology from this book all around me. It is a little dated at 10 years, some of the chapter such as the ones on alpha models felt dated, but I read there is a 2nd edition in the works. There is a lot of math in this book, it actually it just linear algebra a a little bit of expectations. The linear algebra keeps things organized when you are dealing with 500 securities at once.