His own argument is bust in that in that success and failure are themselves asymetric, so it's a moot point.
"Failing" or "not succeeding" is the default and anyone can do it. In fact, the majority of people will never "make it" and most people even who do semi-well will live comfortable but not amazing lives.
"Success" which he seems to judge as perhaps being a somebody or doing something notable follows a power law distribution. It's rare.
Ok, so most people work the 9-5. And what does Taleb have to say about that? He says "ok, well, yes, if you're a slave then IQ seem to predict you'll do better in that particular game". Right. So it is a good predictor of how well you can expect someone to do when they play the game that the vast majority of people play.
So... In other words it's roughly speaking useful.
Don't even get me started on on his term IYI (intellectuals-yet-idiots). Implying that there are people who are intellectuals that suffer no bounds to their rationality nor any partisan or ideological bias. Right. Only an IYI could even come up with such a concept. I see this all the time. Disagree with someone in academia? Oh, well they are a pseudo- intellectual! Or perhaps you might consider the alternative that you just used pseudo-reasoning to reach your psuedo-conclusion.
He draws an analogy between "best measure" proponents and "Value at Risk" proponents.
Ok. Well let's lay out the tools that will help us analyse that analogy. In the book Shortcut John Pollack describes the 5 things that characterize an effective analogy.
1) uses the familiar to explain the unfamiliar
2) highlights similarities while obscuring differences
3) identifies a useful abstraction
4) tells a coherent story
5) resonates emotionally
It certainly resonates emotionally if you accept the premise that it tells a coherent story. It certainly tells a coherent story that relying on a bust metric will catastrophicly blow up in your face if you accept the premise that it identifies a useful abstraction. It identifies a useful abstraction that a metric might not actually be measuring anything real if you accept the similarities and don't look at the differences.
I'm not part of the finance world and don't have a good enough grasp to deconstruct the analogy enough to figure what the differences are and whether it is a good or a bad analogy, but I wanted to lay out the tools to help people do so.
My gut says thats not a good analogy. If only because people say that well it seems to be the best measure we have and he says that's what the VaR guys said. But then he also says, well yeah if you're talking about the domain in which the majority of people spend the the majority of their lives (the workplace) then yes, it does actually seem to have some predictive power there.
He himself is fooled by randomness.