Customer Reviews: Hedge Funds: An Analytic Perspective (New Edition) (Advances in Financial Engineering)
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VINE VOICEon December 25, 2008
Let me start by saying that for someone wanting to learn about hedge funds, this book will still give you a decent amount of knowledge and a lot of empirical results. In fairness, the author has done a good amount of research on the subject, but I did not get the sense of a compelling consensus that these results are robust. What this book is good for is to gain an understanding of the databases that provide useful hedge fund information. So if you want to conduct your own empirical studies, yo will know where to go. This book does not seem to be as exceptional as the author's other books (e.g. Econometrics of Financial Markets).
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on January 11, 2014
An extrem Compact and reliable Source for all kInd (Financial) Investors. To hedge Risk is more important than ever. It covers all parts and is extrem well wrtien! Easy to understand,
Andrew W. Lo needs no introduction if you are working in the Financial Indutsry :)

I love princeton Books, some of them are not that easy to read/understand, but they are extremly well Researched
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on December 14, 2010
While I did appreciate the dialog describing the August 2007 failure I didn't purchase the book for its interpretation of history.

The rear cover assured me this book was "the high water mark in the analysis of hedge funds for years to come". To the contrary, I felt it did not even offer relevant exposure to current practices relevant to hedge funds and quants. To be fair, this 2007 publication is now three years old. The treatment of illiquidity and optimal liquidity was interesting, but stopped short after presenting the theory. IMO, practical implementation concerns and concrete examples set apart the quality texts and I just didn't see that with this book.

Probably worth the $40 or so that I paid for it...but just barely.
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on March 10, 2014
Great book!
Great information with great detail about the process.
Detailed definition of the words associated with every step of the hedge fund process.
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The recent financial "crisis" has many pointing to hedge funds as being one of the many culprits in bringing about the "freeze-up" in credit, along with ordinary banks and insurance providers. In spite of their being around for many decades, hedge funds still seem mysterious to many, and this has caused many to view them with (unjustified) suspicion. Even financial modelers and analysts who work in areas outside of hedge funds sometimes view them this way.

This book is written for the latter class of readers. The author, a respected researcher in his own right and one who many readers may find familiar because of his earlier book "A Non-Random Walk Down Wall Street", gives a fairly detailed introduction to some of the quantitative analysis behind hedge funds. The mathematical formalism used in the book should be familiar to the typical financial engineer, but some of the emphasis, particularly on serial correlations, may be surprising to those analysts who have not had to deal with it in practice.

But the author views serial correlation as being one of the most important characteristics of hedge fund returns, and he gives a fair amount of empirical evidence for his assertion early in the book. He makes it clear however that the presence of serial correlation does not necessarily invalidate the random walk hypothesis (i.e. the presence of predictability in returns), but instead is manifested in the presence of illiquid securities in the hedge fund. Serial correlation thus becomes a proxy for the liquidity exposure of a hedge fund. The author also takes into account the fact that `performance smoothing' may be responsible for serial correlation in the reported returns of hedge funds. A linear single-factor model, the details of which are discussed in chapter three of the book, is used to model these possibilities.

For those readers such as this reviewer who are strong advocates of complete automation of trading in the financial markets, chapter ten of this book should be of great interest. It gives in the author's words a tentative explanation for some of the peculiar events that were happening last year at this time in some of the "quant funds", particularly those that deployed what have been called `statistical arbitrage strategies." What is valuable about the author's discussion in this chapter is that he is honest enough to admit his explanations are tentative, and he avoids the hype of the popular and financial presses at the time. One headline in particular made the point that complex mathematical formulas "failed" Wall Street while another spoke of the "miscalculations" of Wall Street's "math brains." There is no doubt that the events of August 6-10, 2007 surprised many, including some of the managers and modelers of these quant funds, but others believe, correctly, that such large sways in losses should be viewed as part of the dynamics of the financial markets of the twenty-first century. Events like those in August 2007 will just be something traders will have to get used to, until the full automation of the financial markets can be completed, after which any anxieties will arise from those whose fortunes may be depleted from the trading strategies of the machines participating in this automation.

The author does not say much about automation in this article, except to give justified praise to those mathematicians, programmers, and managers who worked together to bring about automated trading platforms. Instead the author wants to enlighten readers who may not have in-depth knowledge of `long/short equity" strategies and their role in the events of August 2007. The mathematics is kept at a fairly elementary level, with most of the space in the chapter devoted to narrative explanations rather than mathematical formalism. The author delegates more of the mathematical details to the appendices. All of discussion in this chapter is fascinating, especially the comparisons of the August 2007 events to those in the Long Term Capital Management debacle in 1998. The latter has been used as a kind of benchmark for the modeling of extreme events in the financial markets, and how tightly coupled different sectors of these markets can be. The author alludes to this coupling in his `unwinding hypothesis', wherein the rapid unwinding of any equity portfolio can affect all other quantitative strategies (so-called "common factor exposures"). The obstruction to validating his hypothesis is the proprietary nature of hedge funds, with each one guarding their own algorithmic secrets passionately, but yet who endeavor always to "reverse engineer" the others.

It is this lack of data and the asserted entanglement between different hedge funds that causes the author to discuss a very interesting tool in the mathematical modeling of creditor and illiquidity risk in hedge funds: the mathematical theory of networks. This reviewer, who has in times past worked in network modeling for several years, finds this an exciting development, and further proof of the interdisciplinary nature of today's modeling efforts. Of course when one is modeling networks one is usually given the network topology and then endeavors to understand the information flow across the different devices (or nodes) in the network. However, when applying networks to the hedge fund industry one does not have information on the network topology due to the lack of transparency. The author of course realizes this and corrects for it by calculating the absolute values of the correlations between the hedge fund indexes over time. This gives him a notion of the "degree of connectedness" in the hedge fund industry, and he gives some (pictorial) examples. Simulations using artificially generated data from Monte Carlo simulations may be of assistance here in studying the degree of connectedness, in lieu of real data from the hedge funds themselves (which may not be farfetched given the regulatory threats hedge funds now face).

Since the author is heavily involved in the analysis of hedge funds it is natural to expect him to devote some space in the book to addressing the question as to whether the quant funds did indeed fail. In this regard he views the events of August 2007 as reflecting the liquidation of portfolios that were constructed using quantitative methods. The strength of quantitative methods remains to be tested, and also successful risk strategies must be devised that reflect the large deviation events that might occur in hedge funds.

This review is based on a reading of four chapters of the book.
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on June 22, 2008
This is a thorough analysis of a number of different hedge fund strategies and a preview of the topics likely to be heavily discussed by hedge fund managers, pension plans as they move into the space, consultants advising plans, and fund of funds players.

Puts alot of meat on the bones of many issues those in the hedge fund business are currently discussing and grappling with in order to refine their business processes.

Very well researched and well written. Good analysis of the debacle of quant funds in 2007.
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