Is Taleb a crank?
falkenblog.blogspot.com
falkenblog.blogspot.com
Is Sam Sethi a nut job ? Also no clue.
Is Dvorak a troll ? Again, it doesn't register, he might be.
What I do know is that "Is X a Y ?" where 'X' is the name of some guy that's in the public eye and Y some hyperbolic term (preferably derogatory) will get immediate traction.
Your basic complaint is that concise and sharp headlines do better than detailed, dull ones? Welcome to humanity.
http://news.ycombinator.com/item?id=771303
For the record, I think Doug Engelbart is an absolutely amazing visionary and a person to who we all owe more than we probably are aware of.
You're annoyed that sharp rather than nice fluffy headlines work. You know what I'm annoyed about? How pointless meta-whining like this floats to the top. I was looking forward to hearing from some finance savvy types.
To call people names in order to attract attention to your 'prose' (I use the word lightly) is a pretty low tactic.
It's false advertising just the same, because X really isn't a crank or X would be spending his time in an institution with rubber walls.
Disagreement does not have to be expressed in such terms.
It's been the "meme" in far more than HN headlines for years, though.
Coming up, are swing sets potentially hazardous for your children? That and more, after the break.
Even though we all know what the "answer" is, the fact that it's phrased as a question activates some stupid part of our lizard brains that will keep us glued to the tube.
That is true.
But I'd hope for HN to be populated by people that have a larger part of their brain switched on than the 'lizards' portion of it and a glut in this type of titles in the last week or so is what prompted my post.
I think allegations of "crank"-ness were discussed until about a year ago. September vetted him. End of story.
In another post on his blog, he describes the financial regulation of the market 1930-1970 as a "failure" based on the rent-extraction which the specialists derived. Never mind the stable growth of the economy during much of that time and the various financial disasters since then.
Did it occur to you that Taleb's frequently inflammatory tone might have something to do with this?
Actually, Taleb continuously laments how amazingly difficult it is to stay objective and analytical, especially when it comes to assessing risk.
Taleb's key point however, was that existing economic models depend on using Gaussians for modeling probability distributions, but that Gaussians are only useful in SOME cases. Real world behaviorally driven events rarely fit into a neat statistical framework, so don't try and force them to, you'll just get bad results out of your model.
I would recommend reading his fooled by randomness book as well (and I may be remembering details from that one as well in this comment).
Mandlebrot makes serious criticisms of the standard models of stock and other valuations - these boil down to saying that the "tails" of market changes are going to be larger than the current models.
The simplest example is CDO's. If you believe in short-tailed, uncorrelated stock market changes, you can argue that the stocks of five different tripple-A rated major corporations have a zero percent chance of simultaneously declining. And you similarly combine together even poor quality bonds to create a "synthetic" bond which also supposedly has a nearly 0% chance of failure.
If you believe in long-tailed, correlated stockmarket changes, you believe that the chances of such bonds failing is much higher.
Guess what actually happened?
I would criticize Taleb, however, for not bringing the issue of complex random processes to the fore. I think he wants to make his ideas very accessible but the problem is that he looses the key difference between short-tailed and long-tailed distributions, since short-tailed distributions DO exist in reality, especially physics and so we're not talking generic randomness when looking the problems of understanding markets and uncertainty.
The claim is that people using the models are well aware that the gaussian distribution is only an approximation, and that substituting fatter tailed distributions into the models don't actually affect the outputs very much.
Do you think that, perhaps, the massive collapse of the financial system in the past year might at least cast a bit of doubt on whether that "awareness" translates effectively to behavior?
The approximation is not done for closeness, because they are not close at all, but for convenience and simplicity. Probability theory is amazingly difficult when you are dealing with infinite variance.
Isn't this basically what the entire "Black Swan" book is about? The difference between what he calls "Mediocristan" and "Extremistan", and that physical reality is in Mediocristan, is the basic concept he starts out with.
As for who is right, frankly that's going to take a lot more digestion...