
A critique of The Black Swan - biohacker42
http://www.stat.berkeley.edu/~aldous/157/Books/taleb.html
======
thomaspaine
Taleb raises a lot of valid concerns about the state of mathematical finance.
You wouldn't believe the number of financial models that assume normal or log-
normal returns, despite a vast amount of evidence to the contrary. Value at
Risk (VaR) is a terribly deficient risk metric, and I've never met anyone who
actually believes that Black-Scholes is an accurate model for predicting
options prices, yet both of these are widely used in the financial industry.

My problem with Taleb and all the attention he's been getting lately because
of the financial crisis is that I think it's a logical jump to go from those
criticisms to "these models are bad, because of black swans". Black swans are
defined as unpredictable random events with large impact. 9/11 was a black
swan, but I don't think that the financial crisis we're seeing today is a
result of a black swan. Insurers ignored systemic risk and over leveraged
based on bad asset pricing, but were those assets priced poorly because of
black swans? I think that's a tough argument to make, because mortgage
foreclosures don't seem nearly as unpredictable as say, terrorists flying
airplanes into buildings.

There also seems to be a bit of observation bias in concluding that events are
black swans. Prediction markets can't be right 100% of the time. To quote the
article: "What does it mean to say such a prediction is right or wrong? In
2008, the day before John McCain was scheduled to announce his VP choice, the
Intrade prediction market gave Sarah Palin a 4% chance. Was this right or
wrong? Unlikely events will sometimes happen just by chance."

~~~
yters
What other models can they use, though? Every other distribution assumes even
more about the problem domain, and would thus correlate even worse with black
swans. Sounds kind of like a no free lunch theorem for finance.

Anyways, do you know if anyone is trying to come up with something better?

~~~
thomaspaine
There are other types of distributions which fit black swan type data better,
such as power-law distributions, Gumbel distribution, etc. I don't know if
research in extreme value theory is still a hot topic, but it tries to address
these problems. Here is a paper on risk management and extreme value theory:
<http://tinyurl.com/aa7t6m>

Here is a nice paper on risk measures, and points out some of the problems
with VaR: <http://tinyurl.com/ar3336>

My apologies if you're unable to grok the contents of these papers...they're
both a little technical but I can't think of anything off the top of my head
that's more accessible.

------
kurtosis
Statistical natural language processing is a very prominent example of a field
which has developed effective methods for coping with "black swans" or the
occurance of improbable events that have never been seen before.

If you take any large corpus of text and start counting the frequencies that
different words occur you will rapidly notice that a _huge_ fraction of the
words have never been seen before or occur only once. Biblical scholars called
these words _hapax legomena_ instead of _black swans_. Methods for estimating
the probabilities of these events go back to Alan Turning and his codebreaking
work at Blechley Park. One need not assign zero probability to unseen events a
la maximum likelihood.

Taleb's rants against VAR and mediocristan have always seemed like borderline
straw man bashing to me. Sure there are many fools who believe in the gaussian
or lognormal returns model, but the best knowledge in the field doesn't make
these assumptions. Why doesn't he give authors like bouchard and potters who
have built on mandelbrot's work their due? or does he?

~~~
navanit
I'm assuming you're referring to Jean-Philippe Bouchaud and Marc Potters.

Taleb does give credit to them in terms of them understanding the presence of
fat tails and focussing on the failure of the gaussian. However, both Bouchaud
and Potters, coming from physics backgrounds, believe that the tail-exponent
can be calibrated accurately from a finite sample-set. When in fact estimating
the tail-exponent (the 'alpha' of a power law process) is fraught with small-
sample effects and one cannot reliably make decisions even when you do come up
with an estimate of the tail-exponent. This is Taleb's main beef with the
breed of physicists with power-law models.

The best paper to understand this is: Weron 2001: "Levy-stable distributions
revisited: Tail index > 2 does not exclude the levy-stable regime"
<http://citeseer.ist.psu.edu/448515.html>

More on my website if you're interested: navanitarakeri.com

A Black Swan is not just a rare event - it is defined as a rare event with
_high impact_.

Statistical NLP may handle rare occurrences well (are you talking about
smoothing?), but, by it's very nature, a rare event in a block of text is not
going to wipe out a library now, is it? So the appearance of a rare word in a
block of text is hardly in the same class of problems as epidemics, wars,
market crashes etc.

~~~
kurtosis
Thanks for the interesting reply. Perhaps I'm guilty of not reading Taleb as
carefully as I should have! I definately respect the guy's technical chops -
he was mandelbrot's student.

I'll think a more critically the next time I see a straight line drawn on a
log-log plot. I remember reading a sermon by cosma shalizi chastising
physicists for making basic errors when estimating the exponent of power laws.
I'm sure there's a lot of suspect results in the literature due to the error
that you described :) maybe even a few bank failures.

Regarding the impact of rare words: misinterpreting certain rare words like
"teratogenic" or "mesothelioma" could conceivably have a pretty high impact!

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biohacker42
This is a very good response to Nassim Nicholas Taleb.

In fact, it may have already been on HN, that's probably where I first read it
and have been trying to find it again, ever since.

Taleb is now turning up almost everywhere, so I thought people might find this
interesting.

~~~
hardik
You might be referring to this: <http://news.ycombinator.com/item?id=353264>

------
radu_floricica
This isn't really a... well, it is a critique in the european sense, but it is
not really a rebuttal. Most of it agrees with NNT, and when it doesn't it's
usually on a matter of form.

~~~
Agathos
Wait. Are you saying "critique" and "rebuttal" are synonyms? I never thought
so, and I've never even been to Europe.

------
lgriffith
Calling an event "random" does not mean its causeless. It simply means its not
predicable. Its not predicable because we don't know and/or haven't measured
the relevant causes. Hence, Black Swan events are caused.

Perhaps it would be an interesting and profitable exercise to look for and
measure causes of Black Swan events.

~~~
cdog46
So long as people continue to confuse explanation with description-we'll have
confusion. Math is description; science is description with comparison and the
contrasting of said description(s). Then what is explanation? I have no clue
but to say it is part of consciousness, and,in the case of homo sapiens,
partial consciousness. To say that us(humans) with our four dimensional rules
of calculation & perception can "know" the how of everything is no more
proposterious than to believe the earth is flat. Put another way-scientists
who too often reject a new theory put forth that challenges current theories
or assumptions-it reminds me of religious zealots defending any challenge to
their dogma

