When we were taking principles of investment finance in
college (centuries ago), we learned various ways of valuing shares on the stock
market. Mostly this was because (as we
were taught) the easiest way to buy a company is to purchase its shares on the
secondary market. (It’s not. The 100% S-Corp ESOP is, under current law,
the best way, but it doesn’t apply to anyone who doesn’t work in that
particular company. . . .)
Anyway, the market is supposed to function to determine the
real value of a company based on its past performance and future projections. There is, however, a lot of slippage, due to
factors such as insufficient information, emotionalism, and interference in the
free market.
 |
| Peter Lynch |
Your job as a financial analyst is, presumably, to decide if
the market is right or wrong, and make a decision accordingly. You look at the company, the product, the
market, and overall economic conditions, and invest in what you know, whether
in your own company, or in others. This
is the approach later popularized by Peter Lynch, author of One Up on Wall Street (1989), Beating the Street (1994), and so on.
Lynch’s approach, which stresses the importance of “local
knowledge” (a more realistic “small is beautiful” system than that of E.F.
Schumacher), presumes a rational market.
This, in turn, implies a free market, a sound financial system, and a
uniform and stable currency. “The
Street” (Wall Street) is not, in Lynch’s system, the most important or even the
most accurate gauge of the real value due to the lack of local knowledge.
By knowing more than the market, an intelligent investor can,
in theory, purchase a solid company for the long haul, while a canny speculator
can (again in theory) make some spectacular short-term gains through long
sales. A “long sale” is
where you purchase an undervalued stock, and wait for the market to recognize
the stock’s true value, whereupon you sell and realize a gain from your
superior knowledge.
Interestingly, Lynch avoided the short sale approach, which
is key to the success of a hedge fund. One
gets the impression he considered it a trifle shady, and counter to the
attitude of a real investor or a savvy speculator. (That’s just an impression, however. For all we know, Lynch may think short
sales the greatest thing since sliced bread.)
Unlike a traditional long sale, a short sale is when you
believe a stock is overvalued and will soon go down in price. You borrow blocks of the overvalued stock and
sell it. You then wait for the stock to
drop in price, whereupon you repurchase the same number of shares you borrowed,
give them back to the lender plus a rental fee, and pocket the difference.
 |
| "Profit, profit, über alles. . . ." |
You can see the difference immediately. In a long sale, the amount you can lose is
limited to what you paid for the shares if you guessed wrong, but the potential
profit is limited only by how high the price of the shares goes. In a short sale, the amount you can gain is
limited to the value of the shares when you borrow them, but the potential loss
is limited only by how high the price of the shares goes if you guessed wrong.
Why, then, are profits so much greater on short sales than
long sales?
Simple. You need
money to be able to purchase shares and hold them until the price goes up in a
long sale. You don’t need anything other
than someone willing to lend you blocks of shares for a short sale. Your only investment in a short sale is the
rent or fee you pay to borrow the shares, and the transaction fees you pay to
sell the shares and then buy them back.
A profit of 100% on a long sale is astoundingly good, and could take years to realize. A profit in the tens of thousands of percent
on a short sale is average, and with today's computer trading can take microseconds.
This is how hedge funds make such enormous profits. Combining short sales with computer programs
that exercise calls (buy orders) and puts (sell orders) in microseconds, a
tiny cash investment can be multiplied by hundreds of thousands times the
actual cash required to initiate the transaction.
 |
| Snickering all the way to the bank. |
For example, a hedge fund borrows a million shares of X
corporation at $100 per share, for which it pays $1,000 fee. It then sells (puts) the shares for $100
million and another $1,000 fee, ending up with net cash of $99,998,000. The stock starts to move up, but the hedge
fund has programmed the transaction to purchase (call) the moment the shares increase
by, say, a tenth of a cent. The fund cuts its
losses and repurchases (calls) the shares for $100.001 per share and a $1,000
transaction fee, and returns the shares.
Total loss to the hedge fund: $103,000.
Peanuts in this game.
Now take that same million shares at $100 per share borrowed
and put for a net of $99,998,000.
Instead of rising, however, the stock starts to drop. It goes down to $99 per share in less than a
minute, and then recovers and even increases to $110 per share in another
minute. Did the hedge fund lose in
excess of $10 million in two minutes?
No way. The hedge fund operators
programmed their computer to call shares the moment the decline stopped and the
share price started to go up. They didn’t
call at $110, but at $99.001 per share.
Instead of losing more than $10 million on that short sale, the hedge
fund made $996,000 in one minute.
Now multiply that by the number of times the shares go up
and down that day, and assume that the hedge fund borrows and puts the shares
every time the price drops by 0.1¢, and calls and returns the shares every time
the price stops dropping and increases by 0.1¢.
Even if the price remains relatively stable and fluctuates only a dollar
or two all day long, and even if it
only guesses correctly half the time (not likely if it only buys after the
shares have already declined by 0.1¢), the same blocks of shares could be traded hundreds of
times a day.
 |
| Not "Big Business", but Big Money. |
This is very crude, of course. A computer program can be written so that a
minor fluctuation of a price that does not take it back up to within 0.1¢ of the initial
price will not trigger a call unless the decline has been sufficient to garner
a certain profit, and so on. A program
that is sufficiently sophisticated can ensure that a hedge fund always wins, whether the market for a share is going up or down.
For example, let’s go with the above assumptions, but also assume the shares are traded a hundred times in
one day, the stock declines by $1 each time, and gains by $10, and the hedge
fund only guesses correctly half the time.
At the end of the day, the hedge fund has made $44,650,000 by short
selling a stock that is increasing in value!
Increase the drop to $2 per share each time, and the profits double, $4
and they quadruple, and so on.
Thus, on shares that end the day at the same price at which
trading opened, $100 per share, a hedge fund could make in profits many times
what the shares are worth! On a wild
trading day such as Wall Street has been experiencing with increasing
frequency, a hedge fund can make billions of dollars in profits while risking
virtually nothing.
And you wonder why no one on Wall Street is too concerned
about the fact that banks aren’t lending to businesses that produce marketable
goods and services that real people use?
Why should they? They make much
more money creating money and siphoning their existing reserves into the stock
market to gamble.