Customer Reviews

Nerds on Wall Street: Math, Machines and Wired Markets

5 star:		(13)
4 star:		(5)
3 star:		(2)
2 star:		(0)
1 star:		(1)

 

 

With all due respect to the previous Amazon reviewers, it's hard to believe they both (a) read this book and (b) have any familiarity with Wall Street technology. The book is a collection of articles written for technology magazines from the mid-80s to the mid-90s. Even within an article entire paragraphs are repeated, and the same idea in more or less the same words can often be found a dozen times or more in the book. This is interspersed with apparently random cut-and-pastes from the Internet and lots of tiny black-and-white pictures which the author tells you are only meaningful with color and animation. You get the feeling the author cleaned out his desk, and decided to make some money from the stuff he didn't want anymore.

There is some useful information in here, and the author does know a lot about automated equity trading before the advances of the late 90s. The trouble is it's not presented in coherent sequence and the technical level is too uneven. For example, it is asserted five separate times that garbage collection is a problem for LISP, without any background material. Anyone who knows what garbage collection means in this context, or has worked with LISP, already knows this and will get annoyed at even the second repetition. Anyone without that background will find the repeated explanations meaningless. There is nowhere near enough technical information for nerds who want to understand Wall Street (or the Wall Street of 20 years ago) or Wall Streeters who want to understand nerds, but there is far too much unexplained jargon for non-technical readers.

Another complaint is the author makes significant errors when he steps beyond his expertise, which is often. For example, he claims if you have 1,000 statistical results significant at the 5% level, 50 of them will be false. The correct statement is if you test 1,000 rules with no predictive value, you expect 50 of them to show significance at the 5% level. The number of your significant results that are false depends whether you start with rules that are mostly useful, or mostly random. This is the key insight to the concept of data mining, the author's misunderstanding makes his chapter on the subject misleading.

Another error is the claim that futures markets were developed to allow farmers to lock in prices. This is false historically (no farmers were involved in the creation of futures markets, farmers have never been big participants and have often tried to have them shut down, when farmers do transact it is much more often to double up their bets by buying the crop they grow than it is to hedge) and anyone who believes it misunderstands the economic function of futures. That's dangerous if you also have a computer that can send trades to financial exchanges. Professionally, the author stuck to equities so it didn't matter to him, but it could matter to his readers if they rely on his account.

There is one up-to-date section at the end, which the author admits was tacked on to make the book more relevant, even though he knows nothing about the topic. His angry rant about the current financial crisis appears to be constructed from reading the first paragraphs of other people's rants. He relies almost exclusively on quotes from politicians, senior regulators and bank CEOs, who all agree it was the nerds' fault. He condemns "complex and opaque" techniques in strong language and great lengths. This from a guy who built black-box trading systems. While it's true there can be a long path between a mortgage dollar a borrower sends in (or, more to the point, doesn't send in) and the end investor, and there can be matches from phantom securities along the way, all of this is done by clear rules which are disclosed. You don't really know what a black box program will do until you turn it on, and its workings are never made public. I'm not defending synthetic CDO-squareds, I'm just pointing out opinions on complexity should come from people who know the field. A non-programmer might look at 1,000 lines of computer code and say it is hopelessly complex and opaque, when a programmer finds it a clear and elegant solution. When disaster strikes, everyone will agree it was the computer's fault.

Then he's "mad as hell" at the irresponsibility of Wall Streeters. Again, without arguing the point, this is a guy who loves the Cold War doctrine of mutually assured destruction, and worked on military projects involving weapons of mass destruction for, in his own words, "the guys in the five-sided nuthouse." The worst financial idea in history does not compare in irresponsibility to supporting the capability to destroy all life on earth, at the direction of people you believe to be insane. In my opinion, the system the author supported and still supports had something like a 10% chance of killing me and everyone else (and still might do it), with absolutely no moral or other human justification. And it was done by people, like the author, who were avenging no personal tragedy, were not hungry or trapped or desperate, who had no great spiritual rationale; just irresponsible nerds with toys.

Finally, the coverage is entirely based on projects the author happened to work on and write about at the time, so a few areas are overcovered and many other areas are ignored. With a good editor to remove the redundancies and sections the author is not qualified to discuss, to order the material and to insist on background explanations, links and transitions, this might be a pretty good account. Until that happens, I suggest you avoid this book.

This book is a fun read, but ultimately somewhat disappointing. I had hoped for a book discussing the various computer related treading strategies used on wall street, but instead I found a widely scattered and outdated treatment of everything from internet market manipulation to green technology. Parts of the book are very good, including its treatment of data mining strategies and the problems with LISP garbage collection, but elsewhere it completely looses the focus. What annoys me the most (and almost compelled me to give it one star) is the extremely bad flow of the text. Readers should be aware that this book is just a collection of prior articles and often these are not elaborated and expanded upon (or even put in context) thus mostly raising more questions than they answer.

However when all is said and done, the book is quite funny and the author does point to many other interesting books and articles, so I will give 3 stars and hope that he will write a better nerd quant book next time.

Wall Street, if you believe Ben Bernanke's testimony to Congress last year, is an "abstraction" to most of us. And if there's one part of Wall Street that is abstract even to large parts of Wall Street itself, it's the world of the quant -- quantitative finance, the guys who develop electronic-based investment, trading and analytical models and systems.

Dave Leinweber has been part of that world for decades, and for years he's been showing up at conferences talking about the world of Wall Street's nerds. Finally, he's put his knowledge and smarts to work to explain it to even the most math-phobic person who wants to understand just what the collision between financial markets and technology means for investors, from the most sophisticated hedge fund trader right down to those of us trying to figure out what to do next with our 401(k). Markets move faster than ever before -- you can now execute a trade in less time than it takes you to start reaching for the telephone (six milliseconds or thereabouts). They also move in ways that the architects of these systems -- increasingly significant players -- don't readily understand themselves.

Most of the people on Wall Street who know and understand these changes and what they mean either don't have the communication skills to make the rest of us understand; others are too busy making money or choosing to keep a low profile to share their wisdom. Those who do end up writing about quants all too often end up in one of two camps: over-simplifying what they do and telling the world how brilliant they are, or over-simplifying what it is that they're up and deciding that they are Dr. Strangelove-style villains. Leinweber's analysis is simple, straightforward and lucid. Above all, it's subversively witty, encouraging the reader to roll his or her eyes at some of Wall Street's absurdities. He takes his subject seriously, but not himself.

I recommend this highly to anyone who has a basic understanding of Wall Street but is fed up hearing about quants, electronic trading, etc. etc. and is desperate to lay hands on a straightforward work that will spell out everything they needed to know and were afraid to ask -- including some questions that they didn't know they needed to ask. I wish that more of the writing on complex financial issues being done these days was as accessible and helpful. Far too much of it feels more like taking your medicine -- or dong the assigned reading for a course you're not enjoying that much.

Full disclosure: I know Dave, read his work in galleys and am overlooking my usual policy of not reviewing books by people I know on this occasion, because I think that more than ever before it's important to draw attention to the tiny handful of books that actually do help readers get to the point where they understand the basics of even complex finance. The more general readers that seek out this book, the better. Best of all, this book may be one part of Wall Street where you can truthfully claim to receive your money's worth in both education and entertainment, and where you won't feel that somehow you've been ripped off along the way...

This book is an amusing overview of the history of electronic trading, the hedge fund business, and some personal anecdotes of the author's experiences as a Nerd on Wall Street. The best way to describe it: if you took the quant chapters of Derman's "My Life as a Quant" and merged it with a schoolhouse rock video of the history of finance as narrated by Groucho Marx. The gags in it are laugh out loud stuff; from the graphical sight gags to the verbal yarks; the author has a gift for turning what most consider a very dry subject into something amusing to read and pretty damn funny. He gets the important cast of characters right; any of these historical things should mention Tartaglia, Shaw, Barr Rosenberg and so on. I suppose Ed Thorp and maybe the Getco guys might have been mentioned, but really, the characters who ended influencing others were well represented in his history: Thorp ran a fairly small shop with no spin offs, and I don't think Getco has had any spin offs yet. I think his descriptions of electronic market making, CAPM, and how hedge funds make money are probably the best you're going to find on those subjects in plain english. The book does concentrate on "buy side" equity strategies; considering the author's work history, it's because this is what he did for a living. That means if you want the more technical side of what he's writing about; Grinold and Kahn or Elton and Gruber are your go-to books. The chapter on market manipulations was also good. I mostly wished he had referenced some more technical studies on the subject -it's something most nerds don't like to think about, and it got my "semi pro" nerd wheels spinning a little bit. While many will not be interested in his tales of applying old school classical AI techniques to Wall Street problems, I was riveted: I had considered noodling with the old AI alien technology myself, back when I was first learning things like expert system shells. I sort of figured people had done so at some point, but finally reading about it from someone who was there was good fun.

I disagree with some of his speculations: I don't think machine translation or related tricks are as important as he does -though such things might be important to the kinds of equity strats he describes. I suspect the people who can do this are useful because of how they think about things (probabilities + machine learning = optimal betting), but I suspect they're more "reading the tape" than parsing meaning from news feeds. I also don't agree with his opinions on derivatives. But, you know, if I only read stuff which I completely agreed with, I'd never learn anything new. For example, his description of a proposal for converting speculative equity in a house into tradeable equity is a very interesting idea, which I had only heard allusions to elsewhere. I don't agree with the idea, as I think inflating speculative bubbles is generally a bad idea, but it's a neat idea anyway. Even neater is his proposal for using the $700billion in TARP funds to capitalize $7 trillion worth of banks, rather than to reinflate a bunch of ivy league screw ups in the surviving investment banks the way we ended up doing. I kind of had a similar idea myself when the poop was hitting the prop, but figured I must be crazy if nobody else was saying it. I'm glad he said it; seems kind of obvious in hindsight, and a better way to inject liquidity than the TARP mess. I don't know why the green bits were in there at all in the last chapter; perhaps a genuflection to the local folkways (the author is a fellow Berkeley resident), but again, this was reasonably fun to read about, and at least broadly related to financial issues.

Over all, this is a great, fun introduction to electronic trading, finance and what a certain kind of nerd does on Wall Street. It's the type of book you buy for family members whose eyes glaze over when you try to explain what it is you do for a living. It isn't a textbook, and that is a good thing: if I wanted to know "just the basic facts," I'd go read something else.

As someone who shares an interest in technology and Wall Street I found this book interesting. Leinweber weaves the reader through a largely unexplored subject of electronic markets. It could easily be the best history book we have of how technology came to play a larger role in markets. Leinweber also offers insights for what the future might look like.

If you're not interested or familiar with technology you'll find this book somewhat disappointing. However, for a geek interested in Wall Street its a fun read.

After my last book review, a reader asked how I was able to read so many books, given my other responsibilities. My answer is this: I keep a book near me at all times. When I get a break, I read a few pages. Over a week, that means a book gets read. That's how I read so many books.

Onto tonight's book: I had a number of friends that liked Nerds on Wall Street, and I liked it as well. The book has a number of strengths. The author explains complex financial instruments in relatively simple terms. The same for complex trading techniques.

The author gives history and background as one that was sucked into computerized finance from a technical background that might have had him in a purer technological role. As I read what he went through, I said to myself, "He was seven years ahead of me." I had my own share of innovative things that I did, but the things done in his era were bigger.

He gives reasonable explanations of how computerized trading works, and what factors they look for in designing trading systems. He talks about the common factors that dominate trading systems, and a few that he knows of but has not published. (He gives a taste, but does not serve up the full dish.)

Like me, he serves up a full plate of data mining disasters. There are a lot of losses to be taken by those who think they have discovered a statistical regularity in the financial markets. The few significant regularities make sense to seasoned observers, and are not consistent. They pay off 70% of the time, and kill you 15% of the time.

On Wall Street, if you are really, really smart, they will hand over to you exceptionally advanced tools that you can use to destroy yourself in a unique and memorable way. So it was for LTCM.


Quibbles

The book is badly edited. Many elements appear multiple times with little modification. It sometimes reads like a bunch of articles that was strung together into a book. The editors should have tried to create something more cohesive.

The last several chapters feel like an afterthought, though many of the ideas presented there are ideas that I have suggested. I have talked about splitting mortgages into smaller mortgages plus equity appreciation rights. I have also suggested creating mutual banks, rather than what was done with the TARP.

All that said, the average reader will learn a lot here. I recommend the book to those that want to dig into how the equity markets became more computerized. For those that want to understand the same for the debt markets, that book remains to be written.

I require my MBA students to read chapters of "Nerds on Wall Street" to gain background for my courses in IT and the financial markets. It is a personal and idiosyncratic history of Dr. Leinweber's experiences during the formative period of our electronic financial markets. It is not academic, but a richly textural view that has more of a firsthand "Liar's Poker" feel. While a number of the chapters are essentially reprints of previously published material, it does offer the reader a firsthand view of thinking at the time and has provided me examples of prior art in patent disputes. It resonates with my students and puts events in context. Having worked on Wall Street and in technology since 1968, our careers are contemporaneous and I can personally relate to his experiences. It's an enjoyable read from a unique perspective.

I liked this book, and I actually spent a few nights reading it in the bookstore before deciding to buy it. As many people point out there are some repetitions in the book. That gets annoying, there are even figures repeated! The author is funny, and provides some insights to the history of wired markets. That's what the cover of this book promises to do and I think it delivers well. I didn't read the chapter on "NOWS Going Green" the whole idea turned me off, and I'll gladly tear out the pages and send them to anyone who is interested.

I got this book at a finance conference yesterday and read it all the way on the plane home. Bear in mind I almost always sleep on the plane from lift off to touchdown, but I couldn't put this one down.

The history sections are simply superb and the well-chosen pictures tell excellent stories. And it is representative of the book in that it gives perspective.

In short, that's what this book offers: a step-back overview of technological progress on Wall Street. The specific chapters also do a great job reviewing particularly important recent and not-so-recent innovations, from textual analysis to genetic algorithms.

And of course, it is quite fun to read.

There are many creative and dynamic individuals that work on Wall Street that use sophisticated mathematics and artificial intelligence for financial trading and who do not satisfy the "nerd" classification. But despite the title of this book, the author gives a very interesting overview of the use of mathematics and machine intelligence in financial engineering. His approach to history however is purely anecdotal, so readers should not expect a detailed study, but rather a work that targets the "general audience", however vague the latter characterization is. There is a lot in the book that is controversial, and many who work in the financial industry may be insulted by some of the author's commentary, but in general he refrains from the vituperation that characterizes much of the current discussion on financial modeling.

The author covers just about all the techniques used to "get an edge" in financial trading, and his coverage of computational linguistics is unusual in that it is typically not discussed at all in books at this level of discourse. Readers will also get more insight into the concept of "alpha" and what it is like to work in the field of financial modeling. Indeed, modelers have been blamed for much of the current "financial crisis", but some have also taken credit for inducing events that they show no evidence for having caused or controlled. The origin of this kind of mental confabulation is not really known, but the author is aware of it when he states that in financial forecasting it is "remarkably easy to fool yourself."

It is along these same lines that the author falters in the book when he blames some of the more "exotic" financial instruments for the "financial crisis". He banters about words such as "pointless complexity" and "monstrously complex" to characterize some of these instruments but at no place really defines, even in a loose sense, of what complexity is. Also, he never gives any quantitative evidence that is was mortgage-related financial engineering that contributed primarily to the current financial situation. It would be very difficult to disentangle the effects of mortgage-backed securities from other derivative securities. This part of the book is therefore its worse, and needs considerable revision on the part of the author.

In addition, the author has too much faith in governmental regulation, as is apparent by his support of many of the regulatory institutions that have arisen in the last 80 years. He is not alone in his fear of a free market though. One need only view the actions of financial executives and their begging for alms from Washington. They tremble at the notion of a free market. They quake at the idea of no governmental agency to cushion them against their follies.

The current schism between "intuitive" and "quantitative" trading is also brought out quite elegantly in this book, and if the author's historical summarization is to believed, one can expect to see more use of quantitative methods in the future. The author's discussion in this regard is additional proof of the Schumpeterian nature of financial innovation in the twenty-first century. This creative destruction of past trading methods is to be encouraged, and hopefully the day will come soon when the Leo-Malamed-type trading is replaced by full automation, by technology robust enough, reliable enough, and intelligent enough to move capital where it should be moved, and to manage portfolios independently of the weak constraints of human intuition.