Customer Reviews

The Predictors: How a Band of Maverick Physicists Used Chaos Theory to Trade Their Way to a Fortune on Wall Street

5 star:		(6)
4 star:		(6)
3 star:		(3)
2 star:		(9)
1 star:		(8)

 

 

I agree with many of the other reviewers. This book is 90% filler. Instead of discussing the topic at hand, we are repeatedly bombarded with a desciption of the weather, the El Paso fiesta season, etc... This is a story about a group of (in my opinion, uninteresting) characters, and not a book on Investing or Science. Not recommended.

This book is less about the market and more about the personal relationships and dealings of a business start-up. I'm surprised that the book lists its category as BUSINESS/SCIENCE when truly it lies in the former. I guess mentioning chaos theory, neural networks and genetic algorithms was all that was needed.

Regardless, it was an entertaining story about a group of physicists, being totally ignorant of the market, decide that they can predict the market. The storyline follows what I would consider typical of any start-up; the fights, arguments, doubts, meetings galore, etc... As I said, entertaining but not too much different from any other story about a start-up.

My two biggest complaints:

1) The back cover from the San Francisco Chronicle calls this book "one of the best books ever written about commodities, currency, and derivatives trading." I don't think they even read the book since this book isn't about trading but all about the traders.

2) The over use of descriptive fashion and landscape. I lost track of how many times we needed to be told who was wearing what and how blue the sky was in Santa Fe. It really got annoying after awhile.

Well I picked up the book as I am interested in complexity science. Most of the reviews here are quite harsh, and probably it was bad expectations management on writer's / publisher's part.

Even though the book sometimes is promoted as an investing book, it is not. It is not meant for day traders who just expect to discover next holy grail of financial markets reading such books. There is no holy grail in markets, but thats another thing. With that said, it may be clear that it is not a TRADING / INVESTIING book.

The book is story of two renowned physicists turning to use their physics, specifically chaos theory, to model financial market. The story part is dealt with great care. I am sure you learn a thing or two reading this book. This book was quite reasy to read and time I spent reading was worth more than had I spent reading a Grisham novel or watching some stupid soap on TV. It is real life here folks.

Bass is not a novelist so I did not expect him write a literary piece here. He has written a true story in a very good way and struggle of Farmer and Packard in estabilshing a company and utilizing their knowldge in a productive way is very cleverly depicted. There are tonnes of other relevant information that come and go, and an intelligent reader would surely pick something here. There is a lot of current history explored here.

With that said, this is NOT a book for the NEXT TRADING SYSTEM, nor does it preach that their system was PERFECT.

Interesting adventures, better than the Hardy Boys! On one page Doyne's replacing the differential in his old van in the desert, several pages later he's suited up (unwillingly, presumably) dueling intellectually with the experts at Goldman-Sachs. In between he's writing checks to keep the fledgling company alive. Like I said, beats Hardy Boys hands down! Bass includes a good description of neo-classical economics ideas, still widely believed by many economicsts far and wide, as in the case of the failed LTCM, not to mention Enron, the IMF, world Bank, and US advisors to Mexico, Argentina, Brazil, thailand, Russia, .... . Significantly, LTCM was guided in part by two Nobel Prize winning neo-classical economists who characteristically proceded implicitly as if there would be 'springs' in the market to enforce the 'no arbitrage' assumption at long (but not too-long...) times. I personally don't believe that the future can be forecast reliably, but then according to a member of The Company they found a small (few %) advantage and sold it to UBS. A gambler with a small bankrole would suffer the gamblers' ruin while trying to bet on such weak correlations. Actually, the hat on the cover looks vaguely familiar, but then what's in a hat?

I am a trader. I traded in the pits for years. I traded over-the-counter. Futures and options, vanilla and exotic. I also hold degrees in physics and electrical engineering from MIT. I was hoping to relate to the characters in this book. I didn't at all.

First, my comments on the book as a story. I was interested at first, but was struggling to get through the last third of the book, as characters were developed that seemed like little more than filler. I tired of the endless descriptions of wardrobe and scenery. And, in the end, we don't really find out what happened. Some reviewers complain about lack of technical detail. The book was obviously not written as a scientific treatise, but as a story, so those readers really have no reason to be disappointed in that aspect.

Secondly, my thoughts about the science and the scientists featured in the book. Nonlinear dynamic systems have been studied by all Wall Street firms, even at the time Prediction Co. was doing it. I actually have a fair amount of distaste for this whole subject. What it amounts to is traders, banks, uber investors, etc. looking for the next quick money making opportunity within the latest development (fad some might say) in informational science. That in and of itself is not a bad thing, but a reasonable quest. The reason most of these kinds of endeavors fail is that unification of Wall Street and academia can only be successful if the researchers or modelers have a firm grasp of BOTH worlds. The models ultimately fail because what is really being modelled is human psychology and reaction. Numbers alone do not tell the tale. There is no (legal) way of knowing that the trader at MS just had a blow up with his risk advisor and is angrily dumping his yen position inefficiently, and that UBS knows MS is also long calls so they begin crushing call volatility since they know MS will liquidate them as well. Sure, a chart may have predicted a squeeze, but the details of the actual trading couldn't have been prophesied. Prediction Co. was running thousands of models? This should be the first tip off that they had no idea what the principal components of the market were. They were shooting in the dark.

This was a perfect example of banker types with no technical prowess whatsoever trying to work with ivory tower types with no street savvy. It doesn't work. "Well, traders and quants work together in most trading firms." True, but this is different because there was no established program or models that the quants were running. This was fly by the seat of the pants almost. While I admire the accomplishments of these researchers in academic realms, they were definitely not cut out to be businessmen with their communistic, hippy, and honestly, somewhat lazy, approach to life. Yes, some succeed, you have your accasional Bill Gates (although I would argue he was extremely business-headed), but not many. Look at the dot-com debacle. Same story.

Lastly, do you really think that anyone who truly tapped into the Holy Grail of trading would actually allow a book to be written about it?

The Predictors, by Thomas A. Bass, is a flawed work. This story is about an attempt to design computer algorithms to detect heretofore unknown market patterns and use them for purposes of arbitrage. It provides an historical account of the creation, development and ultimate success of the Prediction Company, Inc. But in doing so, the author presents a confused portrait of what could have been an interesting story- especially to those interested in the dynamics of financial markets. Before describing the flaws in this book, I should say that there are probably some readers who would find this book interesting. Some, like myself, who have a background in physics (Ph.D.) and in finance (financial planner) will see through the mistakes of the author to uncover an interesting tale of greed, pride and long sought success. For most readers, I fear, their account will confuse and misinform. I should start by observing that The Predictors violates several rules of a good non-fiction book: · There is no author's bio and no Foreward written by a recognized authority of any type. · The author is not trained or schooled in either physics or economics and thus handicapped in telling the story. · And the author neglects to provide footnotes and references.

Bass denigrates the profession of economics by portraying these physicists as saviors of the so-called dismal science, when, in fact, economists have long known about and dealt with the criticisms leveled by these supposed wunderkind Ph.D.'s. An impression is left that the discipline of physics somehow plays a role in what happened; it didn't. What these physicists brought to the table was not science but their mathematical skills. They were not interested in understanding market dynamics; rather they were seeking to isolate market price patterns that would offer them predictive powers. He who can predict the market can, of course, profit from it. Of particular distaste to Bass and the physicists in this story is the economic theory of efficient markets. There is hardly any place in the book where the concept of arbitrage theory is presented. And yet the whole thrust of the Predictors was to find arbitrage opportunities. The important missing concept in this book is that of the feedback to the market from arbitrage transactions which tend to wash out the pattern being exploited. It is a self-canceling phenomenon- just as a fire consumes itself, so does arbitrage. If the Prediction Company trades too heavily on these opportunities or if others discover the strategy and trade on it, the advantage is lost. What Bass completely misses, but I think is understood by these physicists turned day-traders, is the fact that the only way the Prediction Company can survive is to continually uncover newer trading patterns not previously known. If they fail at this their fate may be like that of Long Term Capital Management hedge fund which eventually became insolvent- partly because others picked up and emulated their strategies. With too many players in the game the profits declined and the strategies became useless historical relics. Put differently, the Prediction Company based its transactions on technical analysis and not on fundamental analysis in which the component companies are analysed. As with earlier advances in technical analysis, each new idea for making profits only succeeds for a short time. A subtext of this story, barely described in the narrative, is that of political left-wing physicists learning and eventually embracing the benefits of capitalism. It seems that they gradually realize that their attempts to profit from an imperfect market is not anti-social or evil; rather they are providing liquidity and efficiency to a marketplace that would be less liquid and less efficient without them. Thus in their quest to satisfy their altruistic (originally left-wing) sentiments, these characters become adherents of the market in their new realization that altruism is alive and well in the capitalistic world! All this said, it is not clear that any of these physicists changed their political affiliations. So, yes, they were and still are parasites on the market. But in the ecology of capitalism such parasites are good for sellers and buyers alike- perhaps just as with germs we recognize some of them as "good germs." Likewise among books there are good books. The Predictors is not one of them.

The author has done a great service by documenting some of the ethical anguish that Farmer and Packard went through in developing their company. The arguments they made to themselves to justify their work may seem self-serving to the skeptical critic. In fact in their time and place I think they made a fair and honest assessment of their socially valuable and constructive role in rationalizing the marketplace. Further, by publishing their major insights, they have assured the world that such roles as they serve can have a salutary effect on the economy and by extension on society.

However as with apparently all advanced technologies there seems to be a double-edged sword which in this case neither the author nor the founders of the Prediction Company mentioned in this book. This is exemplified by Dave DeMers's first assignment at Prediction Company in 1995, his visit to the NYMEX oil pit described on pages 272 and 273 of the paperback edition. He discovered that the company was having a significant feedback effect on the market by executing large purchase orders every day at 3:05 p.m. While this market behavior had an obvious adverse effect on the company, there is no reason why other more or less subtle behaviors could not have a positive effect for the company. Some of these behaviors might be unfair, some might be contravening regulations, some might be downright illegal, and all of such behaviors may not even be recognized by the company or the regulators since they may be embedded in the blackbox models generated by the evolutionary algorithms.

In fact it may be that the ethical system that market makers and regulators use to govern behaviors in such marketplaces is inadequate to deal with nonlinear feedback systems in which players employ models that include their own behavior either implicitly or explicitly. The ethical rationalization that Farmer and Packard made for justifying their contribution to the rationalization of the marketplace probably is only applicable when their behaviors have a small marginal effect on any given market. However when they build and use models for 1000 traded equities and have the backing of the large resources of UBS Warburg (which now owns about 25 percent of the Prediction Company) one must consider that an ethics of nonlinear systems needs to be developed to satisfy small and less well resourced market players some of whom may genuinely be the proverbial orphans and the little old ladies and gentlemen from Pasadena.

Obviously there are some relevant regulations already in place such as the up-tic rule for shorting instruments in some markets that the author mentions. They guard against unfair use of this nonlinear feedback effect by which players can take advantage by their own substantial and incrementally large behaviors in the marketplace, whether made with large moves during short periods or spread out and disguised over longer periods. It would seem that by their very nature the evolutionarily discovered models would reveal holes in such regulations. Certainly there's a long history in market finance of such behaviors practiced without the aid of black box models, many of which are now considered unethical and illegal.

Perhaps the next assignment for Farmer and Packard is to develop models for regulators that evolve regulations to fill those holes. Laissez-faire capitalists will not love this approach but as the markets become less transparent with black box models then the game that is being played between the players and between the players and the regulators must benefit from some leveling of the playing field. Otherwise small or less well equipped investors may be driven out of the marketplaces perhaps at great social expense.

The laissez-faire people may want to let the market develop without more regulations. They may see it as a battlefield of wits between quantitative specialists using their own models to detect and take advantage of predictable market behaviors and whomever else might survive. As reported in a Santa Fe Institute workshop linkable from Doyne Farmer's web page, some of the theoretical behavioral economists seem to suggest that the outcome of this approach will divide the surviving players into two camps, the cost efficient predictors and some rational few who just may survive. For example from the concluding remarks of a presentation by Cars Hommes of Amsterdam: "when there are costs for sophisticated predictors boundedly rational habitual rule of thumbs (sic) may survive evolutionary competition".

Well, at least there might be some hope for the rational orphans and the little old ladies & gents.

A great story. It inspired me to create my own web-site (www.stocklift.com) implementing what is called "pairs trading" in the book, which is using the influence of one stock on another.

Of course, there is nothing specific in thee book about the systems they invented - Swiss Bank paid a few hundred million dollars for that, so I had to fill in the blanks by myself.

But the book is worth itself as a narrative of a modern self-funded research effort.

This fun book reminded me of The Electric Acid Kool-Aid Test because I was always learning something funky and new that was way way out there and possibly very dangerous. Doynes as Ken Kesey? Heck yeah! It was also intriguing to me because it showed you how far serious money men and women will go to find the Holy Grail of investing. However, the book's major failing is that it doesn't get into how they made such wonderful gains when everyone around else on Wall Street lost money (i.e. Long Term Capital) big time in the fall of 1998. I thoroughly enjoyed and highly recommend to all. Just don't expect to become a better investor as a result of reading this. Buy a Jesse Livermore book (or mine) for that!

This book's appeal lies in its contrasts. Serious students of nonlinear relationships from academia meet unintellectual money men from Wall Street is one such contrast. Operating in humble surroundings in Santa Fe, New Mexico while supplying information to trade commodities in the financial capitals is another. Informal dressers meet people in power suits is another. In such circumstances, we naturally pull for the outsider, and you will be rooting for the Prediction Company to succeed. When it does, you will feel good. The American dream lives!

If you are looking for a book to help you become a more successful investor, though, this one won't take you very far.

"We look for pockets of predictability, shifting regimens where order can be found merging from what are otherwise highly chaotic time series." This observation in the book builds on chaos theory, a subject that those featured in the book, especially Doyne Farmer and Norman Packard, helped develop. For example, when you look at two fluids that are streaming past one another, the edges are turbulent. When you look at those edges in more detail though, you will see many repetitions of the same pattern (fractals). Having worked first with physical patterns like this, the Prediction Company moves into financial markets to look for fractal patterns caused by human psychology.

I graded the book down by two stars not because it is an uninteresting book, or badly written. The story is quite engaging and is smoothly written. I graded the book down because the book fails to capture the full context of the subject matter, and falls far short of its potential as a result. You get occasional references to chaos theory, computer processing issues, and making money with mathematically-based predictions, but these are only hints. The book should have made these connections as more thoroughly developed themes.

My interpretation of what the Prediction Company is doing is finding situations that occur so predictably (and with so few losses when they do not) that such trades create lopsided risk-reward opportunities. Many securities offer just such patterns, and many money managers search for them. Looking for those that reflect nonlinear relations is done much less often. That concept makes a fascinating story, because computer processing power limits what can be done. How did the Prediction Company get around this problem? We get little information. That's too bad!

After you have finished enjoying this story of the underdogs taking some of the top dogs, I suggest you think about where you know a great deal about something. Where can that knowledge be applied in new places and in new ways? Where could you do this and have a ball? You may at least find a new hobby, as a result. Even better, you could found a new industry!

Keep an open mind!