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Inside the Black Box: The Simple Truth About Quantitative Trading (Wiley Finance) Hardcover – 18 Sep 2009


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Product details

  • Hardcover: 240 pages
  • Publisher: John Wiley & Sons; 1 edition (18 Sep 2009)
  • Language: English
  • ISBN-10: 0470432063
  • ISBN-13: 978-0470432068
  • Product Dimensions: 16.3 x 2.3 x 22.8 cm
  • Average Customer Review: 3.3 out of 5 stars  See all reviews (3 customer reviews)
  • Amazon Bestsellers Rank: 488,808 in Books (See Top 100 in Books)
  • See Complete Table of Contents

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Review

Excellent new book . . . demystif[ies] the world of quant investing, and does so in a way that should be intelligible to any thoughtful investor. . . admirably thorough . . . and highly readable throughout. The book has a logical structure, which gradually builds an ever more complete picture of what it is that quants do, how they do it, and what the issues really are that surround quant trading. Much more than a simple "beginner′s guide" to quants, and it really gets interesting in the final third, where [the author] looks in some detail at the risks inherent in quant approaches and the criticisms of quant trading and how to evaluate them. To find out more about how to evaluate quants, read this book. AR Magazine In "Inside the Black Box," Rishi Narang makes the impossible seem possible: he takes the vastly misunderstood role of the quantitative trading strategy and makes it understandable to those with only the most tenuous working knowledge of global capital markets. How he does so is a sleight of hand no more complicated than patient, consistently eloquent writing, and easy–to–understand, basic examples." Markets Media Online "The book, Inside the Black Box: The Simple Truth About Quantitative Trading , by Rishi Narang, is hands down the best introductory book I′ve read on the topic. Narang does a brilliant job of explaining (in simple English), how and why quantitative trading works. If you are looking for a primer on Quantitative Trading I strongly endorse and recommend this book." TradingMarkets.com "In a new book on quantitative trading strategies, entitled "Inside the Black Box: The Simple Truth About Quantitative Trading," Rishi Narang, founding principal of Telesis Capital, seeks to explain with real–world examples and anecdotes what it is exactly that quants do The book focuses on a few major questions that Narang says are important to understanding the quant world. These include: what is a quant, what are the secrets of successful quant trading, what caused the disasters in quant trading, what role did quants play in the credit crisis, and what is the future of quant trading?" Advanced Trading "You may be skeptical that Rishi Narang will be able to deliver on the ambitious promise of his book, Inside the Black Box: the Simple Truth about Quantitative Trading (published by John Wiley & Sons, 2009). But he does deliver. He tells you, in language that can be understood by most educated people, what a quantitative trading system is and what a quant does." hedgefundsmarts.blogspot.com

From the Inside Flap

Quantitative trading strategies—known to many as “black boxes”—have gained a reputation of being difficult to explain and even harder to understand. While there is a certain level of complexity to this approach, with the right guidance, you can successfully overcome potential obstacles and begin to excel in this arena. That’s why expert fund manager Rishi Narang has created Inside the Black Box . In a straightforward, nontechnical style—supplemented by real–world examples and informative anecdotes—this reliable resource takes you on a detailed tour through the black box. It skillfully sheds light upon the work that “quants” do, lifting the veil of mystery around quantitative trading and allowing anyone interested in doing so to understand quants and their strategies. Divided into three comprehensive parts, Insider the Black Box opens with an accessible introduction to the discipline of quantitative trading and quickly moves on to demonstrate that what many call a black box is in fact transparent, intuitively sensible, and readily understandable. Along the way, it also explains how quant strategies can fit into your portfolio and why they are so important. Whether you’re an institutional investor or high–networth individual, the lessons learned here will help you gain an edge in today’s turbulent market. Some of the tough questions answered throughout these pages include: How do quants capture alpha? What is the difference between theory–driven systems and data–mining strategies? How do quants model risk? What can be learned about investing in general from quantitative trading? And much more. Given both the difficulty of the market environment over the past few years and the negativity surrounding hedge funds in general and quant funds in particular, there has never been a better time to become more familiar with what quantitative trading is really about. With the help of the framework found here, you can gain a firm understanding of quant strategies, discern which are more likely to succeed, and ascertain how to use specific strategies in a portfolio, to help improve the performance of your investment process.

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Front Cover | Copyright | Table of Contents | Excerpt | Index
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Customer Reviews

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Most Helpful Customer Reviews

3 of 3 people found the following review helpful By I. Ayodele on 11 Jun 2012
Format: Hardcover
I picked up this book because I was interested in finding out more about quant finance in a succinct and intelligible manner. As someone who's worked with Quants and Financial Engineers for years, I am aware that much of what is done is submerged in esoteric lingo, and complicated mathematical notations that could easily dampen the zest of anyone interested in getting a broad, but useful overview of the field.

Probably owing to my job as an Asset Analyst, I find structure and flow paramount to effectively communicating how things work, especially to audiences that are generally unfamiliar with investment products or the nuances of trading. On that basis alone, I rate Rishi's book quite highly. He managed to come up with a framework that hung usually distinct areas of financial engineering together, and he took the time to explain each of them in reasonable detail, without over-working any area. That structured delivery is what most mathematics-heavy and very technical investment and trading books lack. The outcome is that only a few people glean anything meaningful from such materials. For those who want more technicality, Paul Wilmott and similar writers are clear alternatives.

My criticism though is twofold. Firstly, there were some editing issues in terms of correct grammar and missing words in some parts of the book. Secondly, certain sections were tediously long. Also as an aside, I did find the use of a feminine character in most, if not all of the examples, an over-kill of political correctness.

All of that said, I still do not think the book is bad in the slightest. It does what it says on the tin, and demystifies quite a number of seemingly complicated financial strategies.
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5 of 7 people found the following review helpful By Maurice on 31 Oct 2011
Format: Kindle Edition
When I first started reading this book, I thought it was shallow and patronising. However, I quickly came to realise that in actual fact it was Rishi Narang's gift for explaining things in a clear and concise manner. Through this book he showed me that, broadly speaking, the range of strategies employed by quants is limited and easy to understand, lacking the complexity that I expected to be explained in great detail. For that, he deserves a great deal of credit. However, I have several issues with the book that prevent me from giving it a higher score:

* It's overpriced, especially for the Kindle edition. At this price, for example, the number of typos is inexcusable.

* Despite its aim of clarity of presentation, I would have preferred and expected more technical details, even if they were left in an appendix. A better publisher description could have avoided this expectation.

* For some unknown reason, throughout the book quants are referred to as the female gender - e.g. "When a quant intervenes with the execution of HER strategy, it is most commonly to mitigate problems caused by information that drives market behaviour but that cannot be processed by the model" (emphasis my own). A classic case of political correctness gone mad, I found it incredibly jarring given the male domination not only of the financial industry but quantitative sciences like mathematics and physics. Of course there are female quants and I know some myself, but the dissociation made many passages difficult to read.
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2 of 4 people found the following review helpful By antonio on 2 Feb 2012
Format: Hardcover
I thought the book describes more the technical side of Quantitative Trading at the book title seems to go at least demonstrate how the techniques and studies.
I am not an expert in quantitative trading, so I thought the book would tell you more about, for those interested in the subject, called by the title of the book, go to the languishing book brings the nuances of how to operate, create algorithms to trade system.
Thanks.
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Most Helpful Customer Reviews on Amazon.com (beta)

Amazon.com: 45 reviews
67 of 75 people found the following review helpful
Finally, a clear, straightforward, accurate account of quant trading 2 Jan 2010
By Aaron C. Brown - Published on Amazon.com
Format: Hardcover
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.
72 of 88 people found the following review helpful
not recommend this book to a serious quant trader. 30 Dec 2009
By Rajat Bhatia - Published on Amazon.com
Format: Hardcover
Rishi sent me an email in response to my earlier review in which I had stated "This book is written by someone who has never traded himself but has only allocated money to outside fund managers. I would not recommend this book to a serious quant trader."

While I wrote what I believed was true, Rishi informed me that I had made a false claim. From the website of Tradeworx, I understand that Rishi has set up a quant hedge fund with Manoj Narang, who I guess is his brother.

Therefore, here are my edited comments which I hope are more consructive:

Rishi's book is a good managerial overview of quant trading and the quant hedge fund business. However, unlike the book, Quantitative Trading Strategies: Harnessing the Power of Quantitative Techniques to Create a Winning Trading Program by Lars Kestner, Rishi's book lacks empirical analysis of how to build, test and deploy mathematical trading strategies. If the empirical side of quantitative trading could be emphasized in this book over the managerial side, this would be an awesome book.
40 of 49 people found the following review helpful
Not for quants 13 Oct 2009
By S. N. - Published on Amazon.com
Format: Hardcover Verified Purchase
This book is okay. It is a managerial overview of the quantitative trading field. Don't look for serious discussions of technical matters. There are some reviews on the flap which suggest this book can be useful to quants, but I think a seasoned quant will find more marketing material here than research material.
14 of 17 people found the following review helpful
Why did several guys give 1-star to this book? 20 May 2010
By John E - Published on Amazon.com
Format: Hardcover Verified Purchase
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.
8 of 9 people found the following review helpful
Lacks content 1 Dec 2010
By cory macdougall - Published on Amazon.com
Format: Hardcover
This book is well written, but takes you nowhere. Almost all the concepts in this book are found in almost all trading books anywhere. The understandings you'll find in the most beginner style trading books are just "university-ified" to seem brilliant.
When you buy a book on what makes a car work you need it to include more than it's 5 or 6 major components, you want a breakdown of the parts that make it up and how they work. unfortunately this book gives little to no detail and as such is a waste of your money and more importantly your valuable time.
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