On the September 24, 2025, episode of Afford Anything, Paula Pant explained the trouble with judging our decision-making by (short-term or single) outcomes.
I haven’t heard anyone state it more clearly:
There is a distinction between the soundness of a decision itself versus the outcome that that decision has produced.
And what I mean by that is the following:
Imagine two people, you know, Henry and Frank.
Henry runs a red light, and nothing bad happens. He doesn’t get into a car accident. He doesn’t get a ticket, and he reaches his destination faster. So he made a bad decision that had a good outcome.
Frank [on the other hand] does not run the red light. Frank is a perfect driver, obeys every traffic regulation, wonderful, top-notch textbook driver. And yet, through no fault of his own, Frank gets into a car accident.
Frank did all of the right things, yet still had a negative outcome.
Henry did the wrong thing, yet still had a positive outcome.
So how do we judge their decision-making?
Well, we have to judge their decision-making based on the soundness of the decision itself and not based on the outcome. And the same is true in investing. And that’s where the anecdotal case study gets a little fuzzy, [like] “I have a friend who put his entire IRA into two individual stocks and so far has had a positive outcome.”
That’s the equivalent of running a red light.
Sure, the outcome for the moment may be positive, but if you continue to consistently run red lights, it’s not going to work out for you. And if this guy consistently keeps his IRA in just two individual stocks, there’s a high probability that things are going to go really bad.
And so I think a big part of financial education is probabilistic thinking.
Our primitive brains love simple anecdotes and guaranteed, Boolean results (hit or miss).
But reality is more of a scatter plot. Shoot enough arrows and the pattern emerges.
If you don’t have a big enough sample size, you might just have a fun story.
It’s probably not best to make important decisions based on it.
-Carl.