| | |  | Telecommunications & Network Security | Home » » Pairs Trading: Quantitative Methods and Analysis (Wiley Finance) | | | | | | | Description: | | The first in-depth analysis of pairs trading
Pairs trading is a market-neutral strategy in its most simple form. The strategy involves being long (or bullish) one asset and short (or bearish) another. If properly performed, the investor will gain if the market rises or falls. Pairs Trading reveals the secrets of this rigorous quantitative analysis program to provide individuals and investment houses with the tools they need to successfully implement and profit from this proven trading methodology. Pairs Trading contains specific and tested formulas for identifying and investing in pairs, and answers important questions such as what ratio should be used to construct the pairs properly.
Ganapathy Vidyamurthy (Stamford, CT) is currently a quantitative software analyst and developer at a major New York City hedge fund. | | | Product Details: | | | Author:
| Ganapathy Vidyamurthy | | Hardcover:
| 224 pages | | Publisher:
| Wiley | | Publication Date:
| August 30, 2004 | | Language:
| English | | ISBN:
| 0471460672 | | Product Length:
| 9.4 inches | | Product Width:
| 6.5 inches | | Product Height:
| 0.81 inches | | Product Weight:
| 0.87 pounds | | Package Length:
| 9.3 inches | | Package Width:
| 6.2 inches | | Package Height:
| 0.8 inches | | Package Weight:
| 0.9 pounds | | Average Customer Rating:
|  based on 16 reviews |
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44 of 48 found the following review helpful:
 the only good introduction to pairs tradesApr 15, 2007
By Scott C. Locklin
"Selectos nisi das mihi libellos, admittam tineas trucesque blattas!"
When people talk about "quant" stuff, they are generally talking about two fairly distinct kinds of quant. There are the derivatives guys (options sell side & risk hedgers), and the 'statistical arbitrage' guys. This is one of the best books for a larval 'statistical arbitrage' guy. 'Statistical arbitrage' is a term referring to the techniques used by sophisticated hedge funds and trading desks to provide 'risk free' returns. I stick in the scare quotes around these phrases, because they're not really arbitrage, though they can be pretty decoupled from market returns. The techniques go well beyond just trading pairs, so the phrase, 'stat arb' is probably with us for good, even though it is often neither stat nor arb. The mean reverting versions of these techniques were largely invented by Nunzio Tartaglia and company (primarily Gerry Bamberger according to Thorp) at Morgan Stanley in the 1980s. Many of his underlings went on to found their own hedge funds, and the secret eventually became relatively common knowledge. Boesky was one of the more famous practitioners of merger arbitrage, which is an older, related technique.
This book is a fun introduction to 'statistical arbitrage,' concentrating on the standard "mean reverting pairs" variety, and a decent explanation of merger arbitrage which he unifies with mean reverting stat arb in an interesting way. These two strategies still form the basis of a large number of high frequency techniques in one form or another. In fact, the book provides enough background material to be useful for all kinds of techniques for finding alpha; it has a very clear treatment of factor models, time series analysis (best low level one I have ever read, anywhere) and what market neutrality is and isn't. He provides a decent amount of discussion of the complexities surrounding tradeability and other practical issues that get swept under the rug in most books.
Sure, there are a lot of specific 'stat arb' techniques he doesn't mention explicitly. He doesn't talk about basket trading plays, index arbitrage, volatility arbitrage or any of the other myriad clever (and often over my head) techniques used by sophisticated fund managers to vacuum up loose change that dumb people leave on the street. So what? Vidyamurthy gives you enough material you can go out and learn the practical details of real strategies on your own. If you're gifted enough, you can go figure them out (and more) for yourself once you understand the material in the book: they're mostly variations on these themes. Why should Vidyamurthy give away the keys to the kingdom for $100? Be happy he wrote the book at all. Presumably, he makes a living actually doing 'stat arb' type things, and his motivation was to have a book to give to his underlings so he didn't have to explain GARCH and cointegration to someone who breathes out of his mouth for the 9,000th time.
Anyone who can't read this book simply doesn't have the intellectual horsepower or attention span to do this kind of trading. The book is almost excruciatingly clear, it is very short, and even does the MBA's the favor of tucking the scary mathematics involving matrices and standard deviations safely away in chapter appendices. I mean, it even has cartoons and funny anecdotes (which are actually very funny: I detect a Wodehouse fan in Vidyamurthy). You have to actually pay attention while you read, and some sections, you may have to read twice. The concepts will not leap off the page and embed themselves into your frontal lobes, but it really isn't that difficult for any intelligent person to understand. I can think of no better introduction to pairs trading, or general alpha quant type stuff than this book. It should probably be on every wannabe quant or trader's desk if it isn't already etched into the fiber of their being.
43 of 48 found the following review helpful:
Excellent BookSep 15, 2004
By Dr. Peter Bruhn
I totally have to disagree with the first reviewer. I would rather say the opposite: the book is mathematically too simple in many places. But on the other hand it is not a statistics book. The book tries to explain complicated matters in a simple way. If you have no idea about stochastic processes, ARIMA-models, cointegration, stationarity,... then this book might not be the right one for you. But honestly: then pairs trading might not be the right thing for you either. Pairs trading is based on statistical concepts. This book only gives a brief idea of what statistical concepts are of use for pairs trading and how to apply them. If you really want to go into pairs trading, you will have to get much deeper into statistics then then this book does or can do. In my opinion the book does a brilliant job in giving you a link between statistical models, pairs trading and financial models (like the APT). I also bought the book "Trading Pairs" by Mark Whistler, and I must say i was rather disappointed, as, to my opinion, the book does not tell you what pairs trading is really about, but the book by Ganapathy Vidyamurthy does.
13 of 13 found the following review helpful:
 Covers the right stuff but poorly writtenMar 08, 2007
By Brett Jiu
"Abcot Press"
I was looking for books on stat arb and risk arb and was surprised that not many titles showed up for my search on Amazon. I eventually bought this book (a used copy) and although the book covers exactly the kind of stuff you want to learn about pairs trading, the writing is very poor and there are way too many places where the sentences don't make any sense, regardless of your math/stat background. This book is not a how-to book. It's a general treatise and not a good one at that. I cannot recommend this book. You may want to check out Tsay's financial time series analysis book which, although not specifically for pairs trading, has all the essential materials.
24 of 27 found the following review helpful:
Good Little Intro into Analyzing Time Series DataApr 14, 2005
By JC
"quant"
This book is small and has around 200 pages with very large font. The math is very simple to follow compared with most of the other quantitative finance books out there. In the beggining of my masters program I thought that statistics was nothing more than mumbo jumbo (as I assumed that the way to succeed in finance was via probability theory, numerical analysis, stochastic calculus, and PDE's). Overall, this book changed my outlook on statistics and how analyzing time series accurately via statistics can help you put together a good trading strategy. Please note that this book is a short refresher and only provides the reader with new ideas. I don't think that if anyone had a succesful trading strategy they would be disclosing their recipes and algorithms in a book.
7 of 8 found the following review helpful:
 Flawed but valuableAug 29, 2010
By Dimitri Shvorob
Opening the book on a random page (p. 14) and seeing it call Norbert Wiener "Nobert Weiner", then get wrong the covariance formula, was a bit in-your-face even for Wiley Finance. Some of my expectations were confirmed - a practitioner author with limited time and writing experience, and no editorial assistance; padding, confused/confusing language, etc. - nonetheless, I found "Pairs Trading" intelligent and thought-provoking.
The core Part II, "Statistical Arbitrage Pairs" [sic] focuses on cointegration between logs of prices: according to the author, an arbitrage opportunity is present when ln(Px) - gamma*ln(Py), for some gamma, is stationary; or, loosely, when ln(Px) and ln(Py) share a common trend. In Chapter 6, (unobserved) innovations in that trend are identified (conflated? consider the required properties of the residual in the two decompositions) with returns predicted by a factor model, and a cointegration coefficient is obtained by regressing X's factor returns on Y's, or vice versa. (On p. 108, the author acknowledges the alternative of regressing ln(Px) on ln(Py), and, surprisingly, nods to measurement-error issues as a reason to pass on this option; I would have thought that working with *estimated* factor returns might face that problem too). To me, this suggests that unless estimated factor returns of X and Y happen to be uncorrelated, the author considers log prices of X and Y to be cointegrated; one searches in vain for discussion of cointegration tests. (Ditto unit-root tests. Leaving statistics aside, factor-model design and estimation looks like an important component of the approach - and is addressed with a half-page-long digest of something the author read in Grinold and Kahn). In Chapter 7, the author revisits the stationarity requirement, mis-identifies stationarity with mean reversion, holds out but never shares a relevant theoretical result (Rice formula?), instead shooting own credibility with a wrong argument/calculation. (I am eager to see code that follows the description on p. 120 and reproduces the plots on p. 121). Sensible points, poor follow-up.
Reader beware. The author is normally saying sensible things, but you want to be careful checking his logic. Overall, an imperfect but worthwhile book.
PS. Appropriately, Economist's Buffett Test (Google it) gives mixed results: it's "Buffet" in the text (p. 182) and "Buffett" in the index.
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