OK, it's probably only in my fevered imagination that
the two pictures above seem to bear a more than passing resemblance
to each other. The one on the left is SmartMoney.com's "map
of the market" while the one on the right is a radar
map of the storm-front that swept through Oklahoma in 1999,
spawning 7 tornadoes as it went and doing $1.2 billion in damage. I
found myself contemplating the connection between weather and
markets while reading the latest issue of
Discover
Magazine last night (Forecast: Hazy (with a
50% chance of error) Why making a science out of predicting the
weather has been a lot harder than anyone guessed it would be
By John Marchese). The most obvious
similarity is that both the weather and the markets
are very hard to predict, and largely for the same reasons.
In both cases we're dealing with complex, chaotic systems that
are incredibly sensitive to "initial conditions." The
weather we will have in any given day, for example, is the result of
interactions among countless billions of molecules in the air, the
land, and the sea. The net effect of those myriad interactions could
only be known with certainty if we could model the movements of
every single one of those molecules in real-time, a feat still well
beyond even the most advanced supercomputers.
Edward Lorenz, one of the fathers of chaos theory, was using computer simulations to study weather
patterns in the 1960s when he discovered that changing the initial
conditions for a given simulation - restarting it in the
"middle" of a prior run and calculating the results to
three decimal places instead of six - resulted in a vastly different
outcome. In other words, very small changes in the
starting point ("initial conditions") will cause a chaotic
system to go in a radically different - and unpredictable -
direction. These findings caused Lorenz to ask the now-famous
question:
 |
"Can
a butterfly flapping its wings in the Amazon Basin
cause hurricanes over Kansas?" |
 |
Like the weather, the financial market behavior we observe in any
given day is the result of untold billions of interactions between
buyers and sellers, all reacting to information of every sort,
including company financials, industry and economic conditions,
politics, world events, you name it. The net result of these
interactions will depend on the "initial conditions" in
effect at any given moment, which is why you will so often see
market commentators offer the same explanation for radically
different market outcomes. For example, the Federal Reserve lowered
the Fed Funds rate yesterday by a half a percentage point and the
stock market went down. A few weeks ago, the Fed lowered interest
rates and the market went up. Aren't lower rates supposed to cause
markets to rise? Well, yes, all other things being equal, as
the economists like to say (actually, economists prefer the more
imposing Latin
phrase ceteris paribus).
The simple fact is that all other things are never equal. So,
unless you know the mind of every one of those 80 million or so
traders, and can tally their thoughts in real-time, predicting
short-term market movements is like predicting the weather three
days out, an endeavor so problematic that the U.S. Weather Bureau,
according to the Discover article, doesn't even bother to keep
statistics.
Does this mean that no useful statement can ever be made about
the future course of the markets? Not at all! Chaotic systems,
including the weather and the financial markets, are still open to
"probabilistic" statements. That is, there are certain
regularities that can be identified. For example, while it's hard to
say how much rainfall we're going to have in a given year, you might
start by looking at the average for the last ten or twenty years.
While this year's rainfall will almost surely be higher or lower
than the long-run average, with each passing year the cumulative
precipitation will begin to approach that "normal" value
(a phenomenon known as "reversion to the mean").
Likewise, many academics believe that the stock markets can be
characterized as following a "mean reverting" process.
This means that investors with longer time horizons - five to ten
years or more - don't need to predict the market's movements
from one year to the next; they can make plans based on the average
expected results over their full investment period. While it's true
that you'll still be subject to "initial conditions" -
that is, you'll have a better outcome ten years down the line if you
started with a winning year than if you'd gotten off to a
"losing start" - you're still likely to experience certain
regularities. Such as the fairly-certain expectation that over ten
years or longer your stock investments will yield a return higher
than those available from "safe" investments like CDs and
money market funds. Another way of putting this is to say that,
while the return to the stock market over any given ten year period
will be different, it will almost always be higher than the
alternatives.
What more do you need to know?
|