Chas Craig, BridgeTower Media Newswires
“You don’t have to swing hard to hit a home run. If you got the timing, it’ll go.”
–Yogi Berra
A prior column regarding countering ambiguity bias cited a National Bureau of Economic Research (NBER) paper entitled “We are all Behavioral, More or Less: A Taxonomy of Consumer Decision Making” by Victor Stango (UC-Davis) and Jonathan Zinman (Dartmouth). The full paper can be found at www.nber.org/system/files/working_papers/w28138/w28138.pdf. An interesting finding from the NBER paper was that loss aversion (explains how the pain of experiencing losses is worse than the joy of accruing equivalent gains) and ambiguity bias, which I described as “analysis paralysis,” were the only two of the 17 decision-making biases examined showing a positive correlation to cognitive ability. I think we can all agree then that that makes those biases especially relevant to readers of The Journal Record.
In The Signal and the Noise (2012) Nate Silver cogently points out that there is a static amount of signal on a given topic, so all other data points simply add to the noise. While we certainly get more of the signal (never all) presented to us than prior generations, we also get so much extra noise that decision-making is possibly worse on average owing to the interplay of information overload and our innate tendency toward the ambiguity bias. Ambiguity bias also informs another emotional bias, overconfidence, which is defined by Kaplan below.
Overconfidence – investors exhibiting overconfidence believe that they can control random events merely by acquiring more knowledge and consider their abilities to be much better than they are. They take credit for any financial decisions that have positive results. Any negative outcomes are attributed to external sources.
So, after over worrying ourselves, upon overcoming our analysis paralysis, we have more confidence in the decision that we make than we ought to? Prior columns have discussed the overconfidence bias and strategies on how to counter it.
The interplay of the ambiguity and overconfidence biases was well illustrated by Nick Colas in the July 1, 2021, Datatrek Morning Briefing in which he cited a 1970s study conducted on eight professional horse handicappers. The researchers had the handicappers list the horse-specific data points they found most useful. First, the subjects received their top 10 choices for the horses in an upcoming race. In the next race, they received their top 20 data points. Finally, they got their top 40 choices. The finding: While the handicappers became more confident in their predictions as they incorporated more information, their predictions did not improve.
Mr. Colas’ advice: “The lesson, profoundly relevant to investing: use the wealth of information available in a 21st century world with caution. More is not always better.”
To further the point and to tie the horse handicapping study back to capital markets, below is an excerpt from Warren Buffett’s 2017 letter to Berkshire Hathaway shareholders:
“Though markets are generally rational, they occasionally do crazy things. Seizing the opportunities then offered does not require great intelligence, a degree in economics or a familiarity with Wall Street jargon such as alpha and beta. What investors then need instead is an ability to both disregard mob fears or enthusiasms and to focus on a few simple fundamentals. A willingness to look unimaginative for a sustained period – or even to look foolish – is also essential.”
All this is not to say that rigorous analysis is a waste of time; it’s certainly not. However, after a certain point, our knowledge on a subject seems to grow at a slower rate than our confidence level, which can lead smart people to do dumb things.
—————
Chas Craig is president of Meliora Capital in Tulsa (www.melcapital.com).
