The slide of the Dow Jones and other financial markets by 35 to 45% in the last couple of months attests to the danger of that philosophy. The idea inherent in Taleb's thesis was brought out nicely by the example of the turkey. Every day for a thousand days, the butcher feeds the turkey, makes sure that the turkey has everything it needs, and after a while, the turkey begins assuming that there is no risk in his life, that he can extrapolate his future investments on the basis of his easy ones of the days before. On the thousand and first day, the day before Thanksgiving, say, the assumption proves rather catastrophically wrong - so catastrophically that it can be said to be very non-linear and disruptive ... especially for the turkey.
Significantly, one of Nassim Taleb's most important mentors was Benoit Mandelbrot, the French economist and mathematician who had been attempting to create a model for cotton futures. As he dug in deeper to the problem, he began to realize that most "random" walks aren't truly random - they actually reflect localized changes that can cause seemingly local linear effects at one scale, and can be self-similar at a larger scale ... but that this self-similarity tended to manifest itself not in overall linear behavior but rather in periods of seemingly linear behavior punctuated by significant disruption.
In Mandelbrot's ground-breaking book The Fractal Geometry of Nature, Mandelbrot laid out a comprehensive mathematical underpinning for the study of "fractional dimensions", or fractals, in which pointed out both the fact that fractal, self-similar systems occur regularly in nature, but also making the emphatic point that fractals are extremely dependent upon initial conditions. He more recently applied these to the markets in his book The (Mis)behavior of Markets.
The Danger of Straight Lines
In linear regimes, models about the future tend to be fairly tolerant of initial conditions. If you start out with a situation that is similar to what another "successful" person started out with, then you'll end up in roughly the same place. The degree of uncertainty involved in those initial conditions can be considered one definition of risk. Put another way, if you consider the landscape of "initial conditions" to be a plane, then you could in theory draw a region on this plane (which can be simplified as being a circle) where the size of the radiation is inversely proportional to the risk involved - its a map where you can do the same things and get the same result.
Risk management assumes in general that this radius tends to grow or shrink as a continuous function - that in times of high uncertainty, the radius of the "safe" zone will shrink, but it will do so in a way that is still predictable. However, what Mandelbrot stated (and Taleb has so eloquently expanded upon) is that this is much like rolling a ball on a carpeted stairwell. The ball moves in a very linear fashion with just minor bumps due to the weave of the carpet ... up until the point where it rolls over the edge to the next stair. This transitional point is as much a part of economics as the smooth rolling parts, but the model, in assuming that the world is linear because it was linear, would fail rather spectacular as the ball goes into free-fall.
Nassim Taleb laid this out effectively in his book, describing what he called the platonic fallacy, a fallacy that had three distinct parts:
Narative Fallacy. The tendency that people have to create a story after the facts in order to use that story as a means to determine the cause of those effects. You see this in financial websites, where any movement at all in the stock market is ascribed to one or two events that can be summed up in a ten word title sentence.
Ludic Fallacy. Structured randomness that games (and economic models) use is in fact similar to the unstructured randomness of the real world. The randomness of the world is due to the large number of potential interactions and the unpredictable breadth of actors for any given interaction, and this in turn means that the randomness is usually far higher (has a higher fractal dimension) than the Monte-Carlo methods used for random walks in most economic models. In other words, a model by nature is a simplification, and that simplification may gloss over a major factor that wasn't obvious at the time, and hence skew results dramatically.
Statistical Regression Fallacy. This is the belief that the structure of probability can be derived from a set of data.
Stochastic methods (which encompasses much of probability theory) is built upon the ideas that narratives are a necessary part of understanding the variables involved in a simulation, that a sufficiently sophisticated model is capable of emulating natural randomness and that there are nice orderly envelopes of functions that can in fact properly be used to create such models - they are in fact the very inputs to those models. Yet if these assertions are in fact fallacies, then the whole of financial modelling is in trouble.
Today's World Is Non-Linear
By all indications (and as unpalatable as his conclusion is to many on Wall Street), financial modelling is in trouble, and with it the financial industry as a whole and perhaps most of the modern capitalist system. Probability theory generally works well in the domain where there are comparatively few variables at work, where the speed of transaction is low enough that information moving through the system can generally propagate fast enough for traders to make reasonably well informed decisions, yet slow enough that such traders can react while that regime of stability still holds.
Computers and high speed networks have changed that irrevocably. A significant amount of the world's wealth is currently shuttling back and forth between millions of moderately sized to large computer systems, trading according to preset matrices of rules that were set up in an ad hoc manner to try to cover as many potential tradition variables as possible - these rule sets were, by definition, economic models, employing the same principles disparaged above, and because the transactions occurred at several millions of times the speed of human thought, there was no more way that human being could possible oversee it than they could oversee a major earthquake as it was happening.
Certainly greed and cupidity played a part - too much money was skimmed off the top with each transaction ... the broker, playing the part of the middle man, was able to turn a blind eye to the increasingly radioactive securities that he was peddling because he was making profits without taking much risk - he was paid for selling the risky instruments, not to take on even more risk as a financial institution. Yet because they were making money, the models all assumed that the radius of risk was far larger than it was, and worse, that circle was shrinking far more quickly than nearly anyone were able to predict - because the regime had ceased being linear. Initial conditions mattered ... and this is where things went awry.
Nassim Taleb made an interesting prediction on Charlie Rose. This prediction was that just as people used an insufficiently non-linear model for the rising market, they are similarly making too many assumptions that the process in decline will resemble that of the last major crisis of this type, the period after 1929, when the US (and much of the world) underwent a protracted period of deflation. However, just as this is the build up was partially a "technological" expansion, so too will the deflation be "technological" - where financial information is still moving far faster than human beings can realistically respond to (or even relate to).
Indeed, there's increasing evidence that most of the real "crash" has already happened, and what we are seeing now is the expanding wave as it makes it's way through the economy.
Several years ago, I had an older model Chevy (a Citation, I believe) in which the timing belt snapped. A timing belt is in and of itself a fairly simple device - it is in fact just a belt, like so many others in an engine, but its role is to make sure that the explosions happening in the pistons occur at precisely the wrong time. When the timing belt breaks, the pistons get out of synch, running faster and independently, causing rocker arms to warp and cooling systems to fail. The engine gets hotter and hotter, eventually warping, usually causing the gaskets that hold the top and bottom of the engine to split apart, and sometimes causing enough damage to crack the engine altogether.
Typically, by the time that the car finally rolls to a stop, the engine is toast, the electrical system is usually fried due to heat and wildly fluctuating electrical current, any electronic system has been turned into so much silicon, and various pipes and hoses have melted into noxious piles of rubber. If you're lucky, you can get out of the car before the engine itself ignites. The single proximate cause, the timing belt, could be replaced for maybe thirty dollars in parts and a couple of hundred in labor, but what has happened is a system failure ... a non-linear catastrophe ... you're probably better off just getting a new car.
Of course, its worth noting that eighty years ago, should something like this have happened, the system itself was simple enough that the car would have been fairly simple to fix ... painful at the time, of course, but doable. Now, we're reaching a point where you cannot solve what amounts to a fractal catastrophe with linear solutions.
There's a saying that I think applies well to economics theory - insanity is the process of doing the same action repeatedly and expecting different results. Admittedly, in a non-linear regime that's pretty much what does happen, but what emerges is usually not the result you expect to happen. The current situation, with car company bailouts and bank bailouts, is increasingly looking like it is a non-starter. The infusion of capital may temporarily ease credit problems, but the timing belt is broken, and the car will soon stall again.
Award Fractal Thinking, Not Linear Thinking
Significantly, the demise of the investment banks and the demise of the automobile industry both come about due to the same factor - rather than concentrating on their core business (the safekeeping of money and the production of competitive vehicles respectively) these two industries had (like the insurance and real-estate industries) become far more focused on making money by moving money around.
It is easy (and definitely appropriate) to point at many CEOs with their outsized incomes that were paid far in excess to their actual contribution, but its worth understanding that this had become so attractive because innovation ... actual invention ... is hard. It's difficult and risky and usually costly, it requires the type of mindset that has become increasingly rare not just in the US but globally. It's usually safer just to take your paycheck and pocket the stock options, because you're sending your kids to college and you need to save for your retirement because that's the way that things are done.
The Obama adminstration hasn't even officially taken power yet, but already the president elect is challenging the status quo in interesting ways - chief among them the proposal to rebuild the US infrastructure for the twenty-first century. While this has free market capitalists gnashing their teeth, it's worth noting that it will in fact be companies that do most of the actual work - the change being that rather than essentially rewarding those who have caused the problem in the first place, what Obama is proposing is to restore what has been lost in this country - honest competitive bidding for US contracts, based not upon connection (for the most part - there will always be a certain amount of nepotism) but upon competence.
It is easy for the "free market" to question the role of government intervention, but most people do not realize that the government typically tends to be one of the largest employers of public and private companies. The aerospace industry effectively exists because of governments, because the cost of producing and innovating airframes would be prohibitive if it was not at least partially subsidized by US development. The same can be said for many industries (including the automotive industry, ironically). However, this role needs to be rethought in the face of the collapse of twentieth century capitalism.
One of the roles of government is to provide incentives for innovation. Businesses tend, by their nature, to be conservative - it is typically better, despite all the marketing hype, to find successful products and push them as far as possible than it is to spend massively in research and development - which is of course a very risky proposition. Usually, beyond a certain size, a company innovates by buying up smaller, more agile companies and purchasing their intellectual property ... usually at the cost of forestalling any future innovation.
Suppose, however, that rather than continuing to feed the bloating and inefficient automobile industry (funny how that used to be applied to government), perhaps what the Obama administration needs to do is establish prizes of $8-$10 billion dollars apiece to design and build new vehicles that work in a carbon-sensitive world, open not only to the established companies but to any corporation capable of pulling it off. The prizes would be awarded on the basis of clearly delineated guidelines, with secondary prizes for alternative technologies that look promising.
Indeed, one possibility here is to open up these prizes so that some (perhaps even much) of this money would come from private investors, who would in turn be rewarded voting shares of stock proportional to their investments, and who would get significant tax benefits for doing so. The automotive industry has long been very competitive in maintaining control by its oligarchy; this would serve not only to break these oligopolies but would also give engineers and lineworkers alternatives to their present work that would position them well going forward.
Yet, it is also naive to look at specific industries as being the source of such solutions. Bailouts, whether of banks or of automobiles, presuppose that the industries are in fact the ones best positioned to solve the problems. However, the solution that a car magnate is going to come up with for the fast-approaching transportation crisis will be to design a better car, rather than to rethink our approach to transportation in general. We've entered a regime, as James Howard Kunstler points out, of oil volatility, where oil prices will swing wildly between extremes of price, which will in turn wreak havoc to oil producers and consumers alike.
Perhaps the best new truck is in fact a dirigible, the best new car a bicycle. Perhaps the financial system needs its own Manhattan Project, one designed specifically to rethink the whole notion of business, finance and commerce.
Successful inventions build on the past, but they do so for the most part by asking the question "X was designed to do this, but what if you combined X and Y to do this other thing instead?" It's a non-linear way of thinking - disruptive and game changing, but often the only way to solve a problem that can't be solved by successive small adaptions. Such inventions are seldom "safe" ... they are risky to the inventor, they may have unintended consequences that can't be modelled, and they almost invariably represent a break from the status quo (which pisses the status quo off mightily) ... but such inventions are also typically the foundation of a new way of seeing problems that lead to solutions, rather than simply satisfying the "Powers That Be".
Think fractally, think non-linear, and help those of your linear friends, neighbors and political representatives who can't conceive that tomorrow will not be like today to understand that linear thinking is a dangerous, deceptive illusion.