THE BEAR'S LAIR The wreck of modern finance
By Martin Hutchinson
Over the past 30 years, the capital markets have been restructured through the
tenets of modern finance in its various forms, which together have gained six
Nobel Prizes (Modigliani, Sharpe, Markowitz, Miller, Merton, Scholes) and might
have generated a couple more (Fama and Black.) This has been enormously
profitable for the financial services sector, which has doubled its share of US
economic output. As we are only now coming to see, it has proved pretty well
disastrous for the global economy as a whole.
The most fundamental error of the modern financial edifice was its assumption
of randomness in market movements, without a true understanding of the
conditions necessary for randomness to hold. The laws of probability and the
idea of randomness were
generated by the 17th century French mathematician Blaise Pascal, who used them
to help in winning card games, roulette and other activities in which tiny
physical variations cause a discrete change in results. Since tiny physical
variations are themselves unpredictable, their results are truly random.
This true randomness almost never holds for economic activities. Some of them
are governed by complex underlying equations, impossible for mediocre
mathematicians to solve, which produce pseudo-random "chaotic" behavior, in
which prices or other variables appear to move randomly but are in reality
mostly determinate. The interaction between economic variables is partly random
(itself partly caused by inadequacies in our ability to measure economic
quantities quickly) and partly determined by these kinds of complex
non-linearities.
Other economic variables are also not random, and may not be governed by
discoverable laws; they are simply unknown. Next year's gross domestic product,
for example, is theoretically determinable from factors we could already know
(plus a few random elements). But it is mostly not random; we simply do not
know what it will be.
Pretending that deterministic (but chaotic) quantities or unknown quantities
are random is a huge category error. If such quantities are not random, they
will not obey the laws of randomness. In particular, calculations that depend
on the properties of randomness, such as Monte Carlo simulation, the Value at
Risk methodology or the Black-Scholes options model, will be quite simply
wrong, often very badly wrong.
For non-random quantities, one of the most important properties of truly random
quantities, the tendency of their distributions' "tails" to disappear at around
three standard deviations from the mean, will not hold. In probability, the
chance of four events happening is the product of their four probabilities; in
fuzzy logic, the alternative analytical system for the unknown, the "belief" of
four events is the minimum of their beliefs. If each event has a
probability/belief of 1 in 10, it's the difference between 1 in 10,000 (random)
and 1 in 10 (unknown).
Nassim Taleb, most familiar to the general public through his best seller, The
Black Swan, previously criticized Wall Street, as in the title of an
earlier work, for being Fooled by Randomess. He had it precisely wrong;
in reality, Wall Street and the economists and "mathematicians" (mostly not
very good ones, or good ones who figured out there was a problem but stayed
around for the money) have been fooled by assuming randomness where it does not
exist.
That assumption makes the equations easier to solve; random quantities tend to
be linear, exponential or normal, the three types of equations economists know
how to deal with. Chaotic quantities generally obey power-series equations, or
even nastier ones, while unknown quantities by definition don't obey any
equations at all.
Financial quantities, mostly a mixture of the chaotic and the unknown, are thus
frightfully hard to model. One has some sympathy. Even Benoit Mandelbrot, a
truly superior mathematician who invented fractal geometry, made devastating
criticisms of others' models in his 2004 The Misbehavior of Markets, but
was unable to come up with a better alternative.
The invention of personal computers, together with the intellectual "advances"
of modern financial theory, from around 1980 caused an explosion of
mathematical modeling on Wall Street. Models were used to price options, to
value complex packages of securitized debt, to manage investments and above
all, to manage risk, even being incorporated into the "Basel II" bank capital
requirements.
In the "Value at Risk" (VAR) risk-management system, for example, the model
calculates the maximum possible loss in 99% of periods covered. Even if the
model worked, that would be a foolish way to manage risk for an entire bank
when the periods are as short as a day or a month; 100 trading days is only
five months and even 100 months is only eight years. While the 200-year life
expectancies of the old merchant banks may have been excessively conservative,
eight years is surely rather too short a life expectancy for banks if the
market is to function soundly.
The VAR assumption, that even in the other 1% of periods the model wouldn't be
too far wrong, is completely and dangerously false. When David Vinear, chief
financial officer of Goldman Sachs, said in August 2007, "We were seeing things
that were 25-standard-deviation events, several days in a row", he was
condemning his risk management out of his own mouth. In a truly random system,
25-standard-deviation events would not just be rare, they would be literally
impossible, of infinitesimal probability during the entire history of the
universe.
Not only are price movements not random, the market is not "efficient". It is
subject to bubbles and periods of depression - indeed one of the most
profitable strategies during the latter, employed by the late Sir John
Templeton and others, is to buy small out-of-the-way stocks at random, since
analysts stop covering the lesser names when business is bad, and their prices
drift down arbitrarily far. (Conversely, that's why many of the best investment
managers, mostly invested in small stocks, did so badly in 2008, down 70% or
80% when the market overall was down only 40%; the market was de-arbitraging as
the financial system fell apart.) As innumerable behavioral finance professors
have demonstrated, expectations are not rational.
The Capital Asset Pricing Model (CAPM) also doesn't work, as many have found to
their cost. On the corporate side, it combined with the tax-deductibility of
debt interest and short-term oriented compensation systems to leave banks and
corporations excessively leveraged. Lehman Brothers shareholders have lost more
through bankruptcy than they previously gained through leverage; business
failure is in itself an extremely expensive process.
Of course, bailouts here, there and everywhere have mitigated the costs of
owning, say, AIG or Citigroup shares, but on the other hand, being a
debt-holder in Chrysler or General Motors has proved unexpectedly expensive, as
the Barack Obama administration has reallocated resources to its union friends.
In the past six months, the resource allocation process has become almost
entirely political, and will remain so until the US government runs out of
money, which fortunately shouldn't take too long.
On the investment side, the CAPM has led to the development of innumerable
phony asset classes, whose returns were supposed to be uncorrelated to the
stock market but which were mostly notable for the hugely greater fees they
provided to their sponsors. Hedge funds depend on excessive leverage and the
continuance of misguided financial engineering; private equity funds depend on
the existence of a thriving public market for takeout; and emerging markets
funds depend on the health and liquidity of the world economy. None of them
diversify risk more than marginally and all of them add huge new layers of
cost. The Yale Model of investment management does not work - except for the
lavishly rewarded investment managers who developed it.
Securitization appeared to be a mechanism that allowed banks to remove assets
from their balance sheets, while providing relatively low-risk, liquid assets
for investors. It also didn't work.
First, banks were left with most of the residual risk, so allowing them to
remove the assets from their balance sheets merely encouraged excessive
leverage. Second, the ratings agencies assumed randomness of outcome in, say,
pools of subprime mortgage assets, an assumption that proved to be laughably
wrong. When mortgage underwriting standards deteriorated, they deteriorated
everywhere, so all pools ended up with their share of almost-worthless "liar
loans".
Even when underwriting standards were maintained, real estate mortgage losses
were not probabilistically independent, since a nationwide housing-price
decline caused an ever-increasing cascade of losses, far beyond past
experience. Housing and credit card loans are not probabilistically
independent, because the business cycle isn't random; in a down cycle they all
go wrong at once.
The largest nirvana for mathematically generated profits was the derivatives
markets. Here the "vanilla" markets were relatively sound, with risks
manageable and finite. They were, however, almost infinitely arbitrageable, so
became a trading desk heaven, with far too much volume for the contracts' real
uses, endless speculative games played, and infinitesimal margins.
Most important, they produced an explosion of counterparty risks so that even
the dodgiest bank or broker active in the markets could not be allowed to go
bust. That problem can largely be solved by Obama's proposed legislation
forcing standard derivatives to trade over recognized exchanges, eliminating
most of the counterparty risk and concentrating the rest in one place.
In order to increase profits, traders devised ever-more complex derivatives
types, the management of which required dangerously false assumptions about
randomness. These more complex contracts up-fronted most of their profit,
leading to bonus bonanzas, while leaving their risks ticking like a time-bomb
through their entire duration of several years - so we may not yet have seen
all the loss explosions this business will produce.
Finally, there were credit default swaps (CDS). As derivatives, these were
poorly designed, because their settlement rested on a primitive auction
procedure that is itself gamed by the major dealers, who use it to extract rent
from the US government and any companies unfortunate enough to near bankruptcy.
As we have recently seen in two cases, Abitibi-Price and General Growth
Properties, CDS deviate even further than most derivatives from the theoretical
efficient-market modern finance ideal in that they allow debt-holders to "game"
the default process itself.
In essence, CDS holders, who if they are also bondholders can vote in the
bankruptcy process, act like spectators at a suicide, yelling, "Jump! Jump!''
and pushing companies into default in order to reap bonanza profits from their
CDS. This is particularly attractive if the CDS were issued by AIG and so
effectively are guaranteed by taxpayers.
CDS also act as highly efficient vehicles for short selling; their cost is so
low in relation to their potential profit and their volume so large that they
can provide huge incentives to unscrupulous speculators to drive viable
companies over the edge - this was part of the problem at Lehman Brothers, for
example.
In summary, the dangers of CDS are so out of proportion to their modest
advantages as risk management tools that it seems wisest for the authorities to
ban them altogether, not something I would normally recommend.
We gave poor Jeff Skilling of Enron 24 years in jail for inventing a new
trading platform that turned out to be unsound. As we peer out from the
wreckage that modern finance has left, one can't help thinking that there are a
number of Nobel prize winners who more deserve such draconian punishment.
Martin Hutchinson is the author of Great Conservatives (Academica
Press, 2005) - details can be found at www.greatconservatives.com.
(Republished with permission from PrudentBear.com.
Copyright 2005-2009 David W Tice & Associates.)
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