All Trading Books

Inside The Black Box

The Simple Truth About Quantitative Trading

Rishi K Narang

Praise for

Inside the Black Box

"In Inside the Black Box: The Simple Truth About Quantitative Trading, Rishi Narang demystifies quantitative trading. His explanation and classification of alpha will enlighten even a seasoned veteran."
—Blair Hull, Founder, Hull Trading & Matlock Trading

"Rishi provides a comprehensive overview of quantitative investing that should prove useful both to those allocating money to quant strategies and those interested in becoming quants themselves. Rishi's experience as a well-respected quant fund of funds manager and his solid relationships with many practitioners provide ample useful material for his work."
—Peter Muller, Head of Process Driven Trading, Morgan Stanley

"A very readable book bringing much needed insight into a subject matter that is not often covered. Provides a framework and guidance that should be valuable to both existing investors and those looking to invest in this area for the first time. Many quants should also benefit from reading this book."
—Steve Evans, Managing Director of Quantitative Trading, Tudor Investment Corporation

"Without complex formulae, Narang, himself a leading practitioner, provides an insightful taxonomy of systematic trading strategies in liquid instruments and a framework for considering quantitative strategies within a portfolio. This guide enables an investor to cut through the hype and pretense of secrecy surrounding quantitative strategies."
—Ross Garon, Managing Director, Quantitative Strategies, S.A.C. Capital Advisors, L.P.

"Inside the Black Box is a comprehensive, yet easy read. Rishi Narang provides a simple framework for understanding quantitative money management and proves that it is not a black box but rather a glass box for those inside."
—Jean-Pierre Aguilar, former founder and CEO, Capital Fund Management

"This book is great for anyone who wants to understand quant trading, without digging in to the equations. It explains the subject in intuitive, economic terms."
—Steven Drobny, founder, Drobny Global Asset Management, and author, Inside the House of Money

"Rishi Narang does an excellent job demystifying how quants work, in an accessible and fun read. This book should occupy a key spot on anyone's bookshelf who is interested in understanding how this ever increasing part of the investment universe actually operates."

—Matthew S. Rothman, PhD, Global Head of Quantitative Equity Strategies Barclays Capital

"Inside the Black Box provides a comprehensive and intuitive introduction to "quant" strategies. It succinctly explains the building blocks of such strategies and how they fit together, while conveying the myriad possibilities and design details it takes to build a successful model driven investment strategy."
—Asriel Levin, PhD, Managing Member, Menta Capital, LLC  

User Reviews about Inside the Black Box: The Simple Truth About Quantitative Trading (Wiley Finance)

There are sections of this book that are interesting and useful. But 75% of it is spent stating what a quant does in very general (and repetitive) terms. It is a very nice intro. to the topic for someone who needs a quick primer. But the treatment of actual strategy building and testing is cursory at best. This is unfortunate, as it appears the author probably has a lot more to offer. -- More of a general primer for non-quants than a resource for aspiring quants

Rishi does a terrific job of simplifying what to many is a complicated strategy. The book breaks the pieces of the "black box" into easily understandable parts. The reader can see that black box strategies are not merely computer driven, formulaic trading, but rather a compilation of well thought out processes driven by portfolio managers. A terrific read and one that I suggest for everyone in this industry... -- Great read!

I don't know whether all 5-star reviews are faked or not, but those 1-star reviews on this book seem very unfair. Almost all those bad reviews have the same complaint: the book is not talking about technical details or actual trading strategies. It is true that this book only gives the basic framework of a block-box trading system, but this is the first book I read that gives the framework so clearly. Also, the contents covered by this book is already given very clearly in the Table of Contents --- nobody is cheating. So, what is this book's fault? Why does this book deserves 1-star rating?

I am currently a Computer Science/Statistics PhD student. My research is generally on statistical data analysis, with a dozen published paper on this topic. To gain some basic ideas of systematic trading and see how my knowledge/skills can be applied, I've read a couple of books on automatic/systematic trading (all are popular and high-rating ones from Amazon). By far, this book is the one gives me most insights about how my knowledge in statistical data analysis can be applied to the field of black-box trading.

In a word, this book gives very nice picture of automatic/systematic/black-box trading. It is general, not covering any technical details / specific trading strategies. But it should be good for graduate students in Engineering/Science to gain a clear idea about systematic trading and how their knowledge can be, generally, applied to the field. -- Why did several guys give 1-star to this book?

This is an excellent book that fills an important need. It describes the nuts and bolts of quant trading without jargon or mystery. The most important point the book makes is there is no grand secret, no deep mystery. Quant traders make money using simple ideas anyone can understand, anyone can copy or come up with on their own; many of which are well-known and published. Too many books either muddy the waters that they may appear deep, or are so technical that people outside quant trading shops are unlikely to learn much from them.

The second major point, which the book makes indirectly throughout but only explicitly in the last chapter, is that simple does not mean easy. Successful quant trading requires extreme attention to details at every stage of the process. While it does not actually require great mathematical ability, people who do not think naturally in mathematical terms or who have not worked extensively in mathematical fields, are very rarely successful. Quants feel why some seemingly trivial things are vitally important, while other things can be safely ignored; without that feel you're flying blind.

The book does something important, it does it straightforwardly and well. Therefore there's not much to say about its good points. The rest of this review is criticisms, to correct the few major lapses. It's intended for people who have already read the book. If you haven't, and you have any interest in this field, buy it now and read the criticisms afterward.

I agree with Liberty4all that several reviews appear to be ballot-stuffing (this review seems to have been removed by Amazon, I don't think that's right, especially as it spawned a useful discussion with people weighing in from both sides). While I understand an author's temptation to ask a few friends to give five-star reviews, I don't approve of one-shot reviewers giving fluff. At least find some friends who review frequently and can say useful things.

The book makes a mess of the distinction between Alpha, which is earned from other active traders, and Beta, which is earned from buy-and-hold investors. What he calls "theory" in a strategy is no more than ad hoc marketing junk. Theory does not mean just saying you exploit a "documented behavioral bias" or "institutional rigidity." It means a real, sensible, testable theory of who is losing the money you're making. You need to know who those people are, why they are doing it and monitor that they keep doing it. Without a theory the only way you know your strategy stopped working is when you lose money, you never have warning, and you never know when it's safe to go back to it. Also, a theory tells you what to do when things stop working, the author seems to suggest that your only options are keep the strategy running, change it or shut it down. Professionals have several layers of backup plans. Theory is what separates a quant trader from a technical analyst.

Risk management is covered only in the portfolio management sense, in which risk a constraint or something to be minimized. Independent risk management is barely mentioned, and completely misdescribed. The author does not know what Value-at-Risk is, any paragraph with that term should be ignored. The first thing to ask any quant trader for is her VaR backtest. She should produce a number every day before trading starts such that she loses more than that amount 1 day in 20. The backtest should show the right number of break days, subject to statistical error, and those breaks should be independent in time and of the level of VaR.

Anyone who doesn't compute VaR or other periodic objective prediction is 20 years behind the time in risk management. Anyone who doesn't backtest isn't a quant (and the toy algorithms the author mentions never pass backtest). If you can't produce a good VaR, you don't understand your everyday risk, what happens 19 days out of 20 when markets are normal, so you can't possibly understand your tail risk. VaR is not a measure of risk, it tells you the range in which you can trust your models. You worry more when it is too small, when your models can only be validated in narrow circumstances, than when it is too big. It's not that you like losing money, but for two strategies with the same return and volatility track record, you trust the one that has survived significant adversity more than the one that has seen only mild days.

Leverage risk is treated only in the sense leverage multiplies your gains and losses. This is not what people mean by the term, they mean the risk leverage will disappear or the terms will change. Model risk is misdefined, it is not the risk of your trading model not working, it's the risk of pricing or hedging models giving bad results. Liquidity risk and redemption risk are not mentioned.

The author has a narrow idea of what quantitative methods can accomplish, and therefore gives quants a pass for losing money when unexpected events occur. Unexpected events are as much a part of modeling as expected events. There is less data about them, of course, and it may not be quantitative data. But if you leave them out of your model because you don't understand them or can't put a number on them, you're a number cruncher, not a quant. A quantitative theory has to account for everything that might happen. I don't mean quants never lose money in an unexpected event, I just mean that there are no excuses. If you lose money because of something, that means you bet it wouldn't happen. You might or might not have been paid a fair price for that bet, but you should have known you were making it.

The discussion of the credit crisis is superficial, it seems more a juxtaposition of phrases from editorials than a description. The account of the quant equity crisis of August 2007 is conventional but weak. The last few chapters appear to have been rushed, the writing style unravels a bit and the facts get shakier.

I think I've just told you everything bad about this book. Note that it's less than 1% of the length of the book. That pretty much sums up my judgment, this is a great book, 99% pure. -- Finally, a clear, straightforward, accurate account of quant trading