Why Predictions Are Often Wrong



We all know how difficult it is to get predictions right.  And even when the forecaster is extremely knowledgeable about the topic—maybe even the world’s leading expert—the prediction is often wrong.  Why does that happen?

In a great post about predictions, Phil Birnbaum notes, “The problem is that no matter how much you know about the price of oil, it’s random enough that the spread of outcomes is really, really wide: much wider than the effects of any knowledge you bring to the problem.” (The emphasis is mine.)  In other words, the standard deviation around the mean is so huge that getting it right is simply a matter of luck.

Rather than rely on prediction (luck), we rely on our systematic process to guide our investment decisions.  A systematic process is not always correct either, of course, but the decisions are made on the basis of data rather than relying on luck.

(Thanks to John Lewis for the article reference.)

—-this article originally appeared 9/23/2009.  The spread of outcomes in any situation is really, really wide, and it seems especially so when politics are heavily involved in markets.  The range of outcomes for the peripheral European debt problem, for example, is mind-boggling.  You’re better off sticking to the data than going with an unreliable forecast.

Source - Systematic Relative Strength