The Old Days

Thirty-five years ago a small group of students met in a seminar room in Ann Arbor.  These students were planning careers that would lead into the quantitative analysis of public policy, an idea much in vogue at the time.  Important public decisions might be made not just on the basis of politics, but on the policy impacts, costs and benefits, and economic efficiency.

The students were taught by leading faculty members at a top resesarch institution, learning about administrative theory, organizational behavior, economics, and research methods.

On this particular occasion the group of first-year students was eager to show their stuff.  They wanted to impress their young professor, a man who would later be recognized not only as a first-rate teacher, but a top scholar in his field.

The professor led the seminar by introducing a series of findings drawn from social science literature.  These were relationships like voting patterns of black males, party identification of former military personnel, and the like.

As he introduced each finding, the professor invited the students to comment, suggesting hypotheses to explain the results.  Straining to please, the students had many imaginative suggestions.  Their ideas would have filled out many journal articles.  They were showing off, and happy to do so.  The professor provided some positive feedback for the thoughtful analyses, and ticked off a dozen or so propositions.

At the end of the seminar, the students sat back, satisfied with their performance.  The professor congratulated them on their creativity and imagination, and everyone sat up a little taller.

Then the prof dropped the bombshell:

The actual findings were all EXACTLY THE OPPOSITE of what he had stated!

The next day’s assignment was to come back with new hypotheses for the other finding.

This is an extremely important lesson.  Analyzing lots of data, with hundreds of possible relationships, will always yield some findings — statistically significant!  Fertile minds can figure out some logic to explain these findings.

That approach is backwards.  Good research begins with theory and hypotheses and then moves to testing.

In one sense it is a shame that Wall Street researchers did not get this kind of training.  If one looks carefully at their reports, it is pretty obvious when a researcher is "data mining" and when there is some theory behind the work.  A key question is: Which came first?

Investing is not Gambling

Since there is a long-term positive expectancy in equity investments, buying stocks is not a gamble in the normal sense — a lottery ticket, a trip to the track, or a basketball pool.  Why do so many investment authors use gambling terminology and analysis?

There are two very good reasons.

  1. Gambling activities often permit an exact calculation of odds and edge (positive or negative).  This means that the action can be simulated, modeled, and analyzed.  The study of risk and reward has drawn many serious economists, mathemeticians, and other scholars into the realm of gambling.
  2. The examples may be easier to understand than those from the investment world.  In explaining to clients why certain ideas are silly, a sports or racing analogy often makes it clear.

William Poundstone’s book, Fortune’s Formula, provides an interesting trip into this world.  I cannot really remember a book featuring both gangsters and academics, both separately and face-to-face.  Poundstone describes the efforts of brilliant scientists exploring information theory, the travels between blackjack and investment management of Edward O. Thorp, and some insight into why certain strategies work and others do not.

Much of the book is a debate over the Kelly Criterion, a method of money management that optimizes the size of individual investments.  Some economists dispute this idea, so there is a lively and informative discussion between the information theorists and the economists.

A mistake made by many investors (and even more gamblers) is a failure to understand risk, even when they have significant edge on a specific trade.  Poor money management cannot turn a losing system into a winner, but it can turn a winning system into a big loser.

Why not wait?

One acknowledged investment strategy for market timing is to stay with the major trend.  A problem with this method lies in the execution.  Can the individual investor "pull the trigger" at the right time?

An interesting example occurred on January 3, 2001.  The Greenspan Fed surprised the market.  Here is the report from the next day’s Wall Street Journal:

"The Federal Reserve’s announcement of a surprise interest-rate cut, at
just before 1:15 p.m. Eastern standard time Wednesday, touched off a record
14.17% rise in the Nasdaq Composite Index, some of the strongest gains of
the past year for other major stock indexes, and a shattering of U.S.
trading-volume records."

The WSJ had an intriguing quotation as well:

"This is the Fed putting an exclamation point on their commitment to try
to engineer a soft economic landing," said James Weiss, chief investment
officer for stocks at Boston mutual-fund group State Street Research. He
called it "dramatic," "striking" and "very significant."

Cisco Systems, a widely-followed tech leader gained 24%.

My experience with most investors, fund managers, and professional traders is that they would have trouble buying after such a move.  You had to be there already.

The question for all of us right now is what confidence should we place in the recent market action?  Since the tough-talking from the Bernanke Fed started, the market is anticipating a collapse in every stock linked to basic materials, heavy industry, and technology.  There is a consensus that the Fed will destroy the economy somehow, although the worriers do not agree on exactly how.  What if they are wrong?

On my schedule is a post showing how little the pundits know about the basic facts of government — the role of the Fed, how they operate, and their philosophy.  I place little confidence in the punditry on this subject.