That’s So Random

cluelessWhen my kids were teenagers, if something was random, that was a good thing.  A really good thing, in fact.  Something funny was random.  A good party was random. Being more than a bit of a fussbudget, I objected to such usage.  I didn’t think it was correct.

But I was wrong. 

The Oxford English Dictionary — which is the authority on such matters — has determined as much. In fact, random got its start (so to speak) as a noun in the 14th century, when its meaning included impetuosity, great speed, force or violence in riding, running, striking, and the like.  Its primary usage was in the phrase “with great random.”

Random as slang eventually showed up in the Hacker’s Dictionary and then went mainstream.  It has become a popular colloquial term meaning peculiar, strange, nonsensical, unpredictable or inexplicable; unexpected. As the OED’s Jesse Sheidlower has pointed out, “It was in the movie Clueless in 1995.”  He also adds that Random House was established in 1925 specifically to publish books “at random,” in the words of founder Bennett Cerf.

I hate it when my kids are right and I’m wrong.  As if!?

Even so, in the 17th century, random started to mean “lacking a definite purpose.”  And by the late 19th century, random came to have the clear and technical mathematical connotation that I favor.  In that sense it means being governed by or involving equal chances for each of the actual or hypothetical members of a population as well as having been produced or obtained by such a process and therefore unpredictable in detail.

In investing, it is that unpredictability that really matters, but so does the “in detail” qualifier.  As I stressed in my last post, there are so many variables involved that investing can’t deal in anything like certainty. We might want or even believe in a sure thing investment, but the best we can do is play the probabilities.  As in The Hunger Games, the idea is for the odds ever to be in your favor.

The concept is pretty easy to illustrate. The probability of drawing any given poker hand is calculated by dividing the number of ways of drawing the hand by the total number of 5-card hands.  Therefore, since there are 4 different ways to draw a Royal flush (one for each suit), the probability of doing so is 4/2,598,960, or about 0.000154 percent. That’s remarkable precision in the aggregate, but we still can’t know when one will be drawn (assuming a fair deck and dealer).  That’s why it’s said to be unpredictable in detail.

On Friday, my poor Padres were trying to come back late against the Colorado Rockies in Denver.  The good guys were behind but had scored and had a runner on second and rookie phenom Jedd Gyorko at the plate.  And Gyorko absolutely scalded the ball.  But it was hit right at Troy Tulowitzki.  Game essentially over.  Had the ball been hit a bit in either direction, the outcome may have been different.  Similarly, a 10-year veteran with a .300 career batting average gets a hit 30 percent of the time, but when those hits will come is unknown and whole seasons can deviate substantially from the norm (e.g., the “career year”).

In football, causing fumbles can be a skill.  But recovering them is largely random and predicated (at least in part) upon how a funny-shaped ball bounces.

In blackjack, a player who asks for a hit on 18 deserves to lose, but very occasionally draws a three.  Or in poker, sometimes a player draws an inside straight.  It’s against the probabilities and can’t be predicted (assuming a fair deck and dealer) — it’s utterly random — but it happens.

In the markets, examples are also easy to offer.  Apple has size issues, surely, and other issues too, but if Steve Jobs hadn’t been struck down by cancer so young, it might still be an investing juggernaut. Sildenafil citrate, now sold as Viagra, was merely a hypertension drug when Pfizer discovered certain significant side effects (essentially by accident) and ended up with one of the more profitable drug ever.  Talk about random!

As Nassim Taleb makes clear, we often mistake randomness for agency.  In fact, the prevalent self-serving bias (crediting ourselves with success and blaming bad luck for failure) depends upon it.  Accordingly, we need to account properly for randomness in every investing situation because, much of the time, it really is so random.



2 thoughts on “That’s So Random

  1. Love this post and how it describes the essential nature of investing. Even when we can attempt to quantify risk, essentially the best we can do is capture 95% of the probability. Quantifying 100% of the probability, if even possible, makes the prediction inherently useless.

  2. Pingback: Knowing What We Don’t Know | Above the Market

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