Trying to Pick Winners

We all know that the outcomes in many activities in life combine both skill and luck. Investing is one of these.  Understanding the relative contributions of luck and skill can help us assess past results and, more importantly, anticipate future results.  It might even help our forecasting skills, but we’d probably be wise not to bet on it.

As I have noted before, in Major League Baseball, over a 162-game season the best teams win roughly 60 percent of the time.  But over shorter stretches, it’s not unusual to see significant streaks.  Since reversion to the mean establishes that the expected value of the whole season is roughly 50:50 (or slightly above or below that level), 60 percent being great means that there is a lot of randomness in baseball.  That idea makes intuitive sense – the difference between ball four and strike three can be tantalizingly small (even if/when the umpire gets the call right); so can the difference between a hit and an out.

To look at it another way, the Tigers were big favorites in last night’s first game of this year’s World Series in large measure due to the pitching match-up.  Detroit’s Justin Verlander is widely regarded as the game’s top pitcher and had been dominant through-out the post-season to that point while Barry Zito is generally thought to be one of the great busts in free agent history. Zito was even left off the World Series roster by the Giants just two years ago.  But last night Zito pitched great while Verlander lasted only four difficult innings as the Giants won handily.  In the words of the great Casey Stengel, Who’d-a thunk it?

Luck (randomness) is a huge factor in investment returns too, irrespective of manager.  “Most of the annual variation in [one’s investment] performance is due to luck, not skill,” according to California Institute of Technology professor Bradford Cornell in a view shared by all experts (Nobel Prize winner Daniel Kahneman talks about it in this video, for example).  Even more troublesome is our perfectly human tendency to attribute poor results to bad luck and good results to skill.

As a consequence, in all probabilistic fields, the best performers dwell on process. This is true for great value investors, great poker players, and great athletes. A great hitter focuses upon a good approach, his mechanics, being selective and hitting the ball hard. If he does that – maintains a good process – he will make outs sometimes (even when he hits the ball hard) but the hits will take care of themselves.  Maintaining good process is really hard to do psychologically, emotionally, and organizationally.  But it is absolutely imperative for investment success.

In what Kahneman calls the “planning fallacy,” our ability even to forecast the future, much less control the future, is extremely limited and is far more limited than we want to believe. In his terrific book, Thinking, Fast and Slow, Kahneman describes the “planning fallacy” as a corollary to optimism bias (think Lake Wobegon – where all the children are above average) and self-serving bias (where the good stuff is my doing and the bad stuff is always someone else’s fault). Most of us overrate our own capacities and exaggerate our abilities to shape the future.  The planning fallacy is our tendency to underestimate the time, costs, and risks of future actions and at the same time overestimate the benefits thereof.  It’s at least partly why we underestimate bad results. It’s why we think it won’t take us as long to accomplish something as it does. It’s why projects tend to cost more than we expect.  It’s why the results we achieve aren’t as good as we expect.  It’s why I take three trips to Home Depot on Saturdays. We are all susceptible – clients and financial professionals alike.

As Nate Silver’s outstanding new book emphasizes, forecasting is really hard.  There are simply too many variables and too much uncertainty (Donald Rumsfeld’s infamous – but accurate – “unknown unknowns”) for forecasting to be anything like easy.  As I keep repeating, information is cheap; meaning is expensive.  For example (per Leonard Mlodinow), we are tricked into thinking that random patterns are meaningful, we build models that are far more sensitive to our initial assumptions than we realize, we make approximations that are cruder than we realize, we focus on what is easiest to measure rather than on what is really important, we build models that rely too heavily on statistics without enough theoretical understanding, and we unconsciously let biases based on expectation or self-interest affect our analysis.

Accordingly, consider the following.

  • No less an authority than Milton Friedman called Irving Fisher “the greatest economist the United States has ever produced.”   However, in 1929 (just three days before the notorious Wall Street crash) Fisher forecast that “stocks have reached what looks like a permanently high plateau.”
  • Many of you may remember a book published in late 2000 by James Glassman and Kevin Hassett entitled Dow 36,000.  Its introduction states as follows.  “If you are worried about missing the market’s big move upward, you will discover that it is not too late. Stocks are now in the midst of a one-time-only rise to much higher ground – to the neighborhood of 36,000 on the Dow Jones Industrial Average.”
  • Also back in 2000, Fortune magazine picked a group of ten stocks designed to last the then-forthcoming decade and promoted them as a “buy and forget” portfolio of their best ideas. Unfortunately, anyone who purchased that portfolio would want to forget it. An investment in an equally weighted portfolio of these stocks back then would have suffered a 70% loss over the next decade. 

For perhaps the most pertinent example of all, Pundit Tracker checked up on this year’s pre-season World Series predictions of 58 pundits from ESPN and Sports Illustrated.  These guys are all paid experts who pontificate for a living.  Yet even though the Tigers and the Giants were among the favorites to win their respective pennants (Vegas handicappers had the Tigers at 3-to-1 odds and the Giants at 7-to-1), not a single one of these “experts” picked the Tigers and Giants to meet in the World Series.  That’s a lot of randomness.

The take-away here is pretty obvious. If your investment approach requires or even includes a relevant forecast of future events, be very careful.  And the more specific the forecast, the more careful you should be.

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11 thoughts on “Trying to Pick Winners

  1. Hey Bob,

    I would be curious to read more about how you see this affecting trading in a market with so much computer based models and trades. At a base level it seems like this move toward computer models would remove human planning bias, but I think empirically this is probably far from true. Is it a case of correlation/cause problems or more like we are baking our previous assumptions into the core programing/software?

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  3. Good article-It took me many years of investing before I learned not to put all my eggs in one basket because I thought I knew what was going to happen. I now diversify against many potential outcomes and sleep much better at night.

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