taleb distribution
the practice of bad driving has what i call a taleb distribution, after one of the themes in nassim nicholas taleb’s brilliant fooled by randomness. a taleb distribution has the property that many small profits are mixed with occasional large losses. overtaking on the inside is an activity with a taleb distribution .
the comments on page 231 on the gaussian distribution remind me of this story where even galton got confused about the tails of the distribution as applied to human height .
that rule only applies to normal distribution. so you would have made an assumption .
we can identify two huge problems to be solved. first, many investment strategies have the characteristics of a “taleb distribution”, after nicholas taleb, author of fooled by randomness. at its simplest, a taleb distribution has a high probability of a modest gain and a low probability of huge losses in any period .
>
the realization that the normal distribution is not the only way to model data
.
the positive square root of the second central moment of the density distribution function will keep being that .
benoit mandelbrot argued that financial markets follow a distribution much more similar to the cauchy distribution (specifically the levy distribution) rather than a gaussian. the problem of course is that the cauchy distribution is pathological in that it doesn' t have a mean or variance, you can calculate similar properties for it (location and scale), but it doesn' t obey the central limit theorem so in practice it can be very strange to work with .
statistical economists or analysts always said that the normal distribution is a simplification and that this simplification has its own problems .
realization by who? if you understand the normal distribution you had damn well better know that there are other probability distributions .
however, a single individual can be richer than the poorest 2 billion humans. so wealth follows a scale independent distribution .
the issue was not just that these distributions displayed taleb characteristics: these market activities were devised with taleb characteristics in mind .
i have several times in this column described the taleb distribution of regular small profits interspersed by large losses. taleb distributions are the basis of the carry trade – which exploits interest rate differentials – and many types of statistical arbitrage. taleb distributions are exploited by traders in hedge funds and at proprietary trading desks .
there are other, less abstruse examples. drinking more than is good for us has a taleb distribution. so does smoking – after all, most smokers do not get lung cancer .
holy grail distribution is a missing piece in almost every investment portfolio seeking protection from tail risk events combined with positive average returns .
exactly. i' m astounded that this basic fact - that financial modelers have been using the wrong distribution for decades is not being denounced. for example, the capital asset pricing model (capm) which assumes that returns fall on a normal distribution .
of what you wrote, but i think you should reread your reply to taleb with as much scrutiny as you read taleb .
there are business lessons to be drawn from the bad habits of french drivers. we need to beware of activities whose outcomes have a taleb distribution – many small gains punctuated by occasional large losses .
realization by who? if you understand the normal distribution you had damn well better know that there are other probability distributions .
kay goes on to add that governments yesterday as well as today appear to creating responses that are once again premised on the tailgating distribution .
people rarely check how closely their data conform to the standard distribution; indeed, many people blindly apply the standard deviation to their data regardless of its distribution! the resulting number is often more obfuscatory than helpful, to the extent that it crowded out more useful summaries .
in other words, we' re using the normal distribution as the workhorse because considering other distributions is, well, inefficient / unproductive .
the name holy grail distribution captures both the difficulty of finding a strategy with these characteristics and the unique value it provides to an asset allocator .
the truth is that most times we don’t know the probability distribution at all. because the world is not a predictable casino game — an error nassim taleb calls the ludic fallacy — the best we can do is guess .
taleb has a good point about people mistakenly interpreting standard deviation (sigma) as mean absolute deviation (mad). i like that he gives some conversions (sigma ~ = 1. 25 * mad, for normal distribution) .
it is hard to deliver returns with holy grail distribution using only replication and generally available asset classes; such returns have to be
engineered
. at the same time, allocation to investment instruments and strategies with holy grail distribution of returns may provide clear benefits of diversification and protection from periodic market - performance shocks .
well, frequentist methods are taking the blame for the most recent financial crisis, such as assuming a normal distribution when the empirical one is fat - tailed .
perhaps the bayesian methods will take the blame in the next financial crisis. such as the error in estimating a non - stationary distribution and quantifying the uncertainty .
[ … ] out scott locklin’s brutal takedown of our favorite blowhard, nassim taleb. the only part i disagree with it where locklin calls taleb [ … ]
i didn’t read taleb carefully enough to know whether he was targeting only quants .
compute - intensive statistical tests, which are data - driven and make fewer assumptions about the underlying distribution, can give tighter confidence intervals and detect statistical significance better .
can we escape the taleb problem? understanding risk is the prelude to managing it. we know instinctively that the tailgating driver is not really smart – and nor is the high - yield bond trader. taleb exploits his distribution by looking for its opposite: trading strategies in securities markets that offer frequent small losses and occasional large gains .
however described, it is the same thing: a distribution of returns that produces frequent small profits punctuated by occasional very large losses. a high proportion of trading – and business – strategies in financial markets have this tailgating characteristic. i call it the taleb distribution, after the author of fooled by randomness (an earlier, and better, book than the more widely read black swan), which gives numerous instances .
taleb' s favorite topic is the
black swan event
which is something that the normal distribution, and the idea of standard deviation, don' t model that well. in a normal distribution very extreme events should only happen once in the lifetime of several universes. of course assuming variation inline with a gaussian process is at the heart of how the black - sholes model calculates risk / volatility / etc .
i sometimes think that progress in the 21st century will be summed up as :
the realization that the normal distribution is not the only way to model data
.
a distribution built from mad will more closely resemble the reality of the s & p returns, and will create more robust models. there are many examples of this .
additionally, i will mention that we do not need normal distributions to make special the idea of standard deviations. in fact, it is the geometry of probability - the fact that independent random variables have standard deviations which
point
in orthogonal directions - which causes the normal distribution to be the resulting distribution of the central limit theorem .
gee, d’ya think so bub? maybe i should go have some acupuncture done to harmonize my narcissism. taleb as schindler? how about taleb as jesus sufferin’ christ ?
very nice! i did have his books on my reading list. but this whole discussion definitely puts me closer to the
waste of my time
side of the distribution .
i never heard about taleb distributiom, is my first time sounds interesting... .
the fact you largely resort to attacking straw men rather than taleb’s actual arguments says everything .
i was initially very curious about your post. finding a substantive argument against taleb’s thinking is actually quite difficult to track down. imagine my disappointment when i discovered your post was mostly an ad hominem review of taleb the man rather than an measured analysis of taleb’s ideas .
ltcm had lots of small up months and a few large down months. this is not detected by the sharpe ratio as it assumes a symmetry in the distribution of returns. – nnt
what is more, his idea of black swans is not original, every experienced investor is aware that stock returns don’t follow a predictable distribution, that the end outcomes are extremely uncertain .
the pareto distribution, better known as the 80 / 20 rule, states that 80% of the effects come from 20% of the causes. for example, in most businesses 20% of clients will generate 80% of the income, 20% of clients will generate the most customer service requests and so on. taleb argues that we’re moving to a 99 / 1 distribution, away from 80 / 20. this shift has profound implications for our economy and society .
on page 240, taleb writes that gauss, in using the normal distribution, “was a mathematician dealing with a theoretical point, not making claims about the structure of reality like statistical - minded scientists. ” i don’t have my stigler right here, but i’d always understood that gauss developed least squares and the normal distribution in the context of fitting curves to astronomical observations. sure he did lots of pure math, but he (and laplace) were doing empirical science too .
you have provided an interesting comment to taleb, but there are several things you are missing .
thank god somebody else out there sees that taleb is as mad as a bag of bats .
people ask why people get the heckles up about taleb, and it isn' t actually about taleb at all. it' s about the, for lack of a better phrase, taleb
fan boys
. bizarre that such a thing exists, but people like having their prophet .
taleb distributions are good when you have experienced only the upside. a taleb distribution led to the crises in the lloyd’s insurance market. excess - of - loss policies – t he lmx spiral – insured other syndicates against losses of unprecedented magnitude. the underwriters pointed out that they had taken in premiums for many years and paid nothing out. you do not have to be as smart as taleb to see the flaw but you do have to be a little smarter than the feltrim and gooda walker syndicates .
yet, taleb’s writing makes all those assumptions. if you can fill in the missing steps, then you will find that taleb provides a strong argument for why and how we got to this point .
thank you. i don' t think it is intellectually honest for taleb to omit this fact .
> also he alludes to his paper with goldstein. it is clear form goldstein and taleb' s manuscript that that taleb is not just throwing these arguments to talk trash about practitioners of statistics. they
many apparently successful traders and business people are still on the upside of their taleb distribution. they are accidents waiting to happen. it puzzled me for years that so many organisations believed they were making money out of proprietary trading in securities markets. these businesses were trading mostly with each other: since there is no perpetual motion, where did the money to fuel the system come from? from taleb distributions .
what taleb failed to mention is that, once properly understood, standard deviation has distribution interpretations that can be much more useful than mad. for example, if the data is approximately normally distributed, then there is approximately a 99. 99% probability that the next data observation will be < = 4 * sigma .
taleb, the non - experts, expert non - expert. or something. too jokes, anyway .
this is actually what i expected to read :
the standard deviation is useful because with the average and the standard deviation, one can fully characterize a normal distribution. however, the standard deviation is less useful a statistical summary the farther away from' normal' you get, and in reality, there is no such thing as a normal distribution, as a true normal distribution is defined on the entire real number line from negative infinity to positive infinity. reality always provides some bound, and it' s often quite distorted from guassian. for instance, a' normal' distribution averaging 2 with a standard deviation of 1. 4, bounded by 0, is quite non - gaussian in many important ways! (not least of which is that you' re going to have to do something to replace the missing probability... )
great article btw. i used to adore taleb’s fbr, but that was before i entered the world of finance and trading. taleb tends to repeat the obvious, and so tbs didn’t do too much for me .
his essential black - swan point is that extreme uncertainties cannot be parameterized by any distribution, that we fool ourselves when we translate “uncertainty” into “risk” as characterized by any distribution. it’s a good point, it’s as old as the hills, but it’s a good point…the rest of black - swan expounds on the biases that comform us in parameterizing risk; e. g. , excel has cells for numbers, so the numbers must mean something
the normal distribution is fantastic in that it does appear frequently in nature, is very well behaved, and has been extensively studied. however a great amount of future progress is going to come from wrestling with more challenging distributions, and paying more attention to when assumptions of normality need to be questioned. of course one of the challenges of this is that the normal distribution is baked into a very large number of our existing statistical tools .
it’s an argument that’s well known, and pretty much irrelevant. as aaron brown put it, “ (taleb’s book) reads as if taleb has never heard of nonparametric methods, data analysis, visualization tools or robust estimation”
second, absolute nails sentiment that taleb engenders, i”ve read his books and i’ve listened to him, but he never seems to get beyond the obvious (fat tails, gaussian distribution…yes…we know that…thanks…) he didn’t convince me that he actually is a true quant with a meaningful, progressive self - critique. this makes sense of the posturing .
but please, keep buying china inc. more money for guys like taleb once the markets come crashing down again .
it would be nice to think taleb’s contribution to intellectual discourse is a net positive. i don’t agree, obviously .
to reiterate, there' s nothing wrong with the normal distribution. we' re not about to retire addition or subtraction just because there are
plenty of people who don' t really realize
there' s more to math .
could you sketch out why similar statements couldn' t be made about mad? my (possibly flawed) intuition is that the expected proportion of observations within n \ * mad should be similarly independent of the parameters of the normal distribution .
the standard deviation and assumptions of normality are so useful because of the central limit theorem. that is, if you have many iid variables which have finite standard deviation the sum will converge to a gaussian distribution as the number of variables increases .
if taleb’s arguments were obvious in the way you suggest, clearly there would not be a market for them. simple .
i understand from the papers that taleb is now in a big fight with merton. i agree with him on that .
for five years until 2004 spitznagel and taleb ran empirica, a hedge fund very similar to universa that in its short tenure generated low double - digit returns. after taleb became seriously ill the duo shut the fund. taleb has since given up money management to teach risk management at polytechnic institute of nyu in brooklyn, write books and advise foreign governments on his theories .
i disagree with your comparison of taleb to popper. popper would write things which occasionally made sense. feyeraband and taleb seem to be more of the “makin’ raspberries” school of disputation. throwing kuhn in there … at least kuhn eventually repented of his sins .
taleb’s antics are what he sells. nobody actually cares about his criticisms of specific models: it’s rare that he actually makes any. were taleb out there criticizing actual quant models, you know, by naming them, then stating in clear unequivocal terms where they don’t work and why, and maybe even points out a useful alternative, i would be a taleb fan. hell, in that event, i would be a taleb sahabah; companion to the prophet. instead taleb goes on television and the ft and blurts out that “nobody knows nuthin. ” as such, the just argument against a stupid head is a clenched fist .
i also like how a lot of the people attacking taleb here, are making exactly the mistakes he describes in his books .
as of late on new year' s day, i have still not heard from taleb via email. just too busy .
nassim taleb on the notion of alternative histories — “the quality of a decision cannot be solely judged based on its outcome. ”
if data is drawn from a laplace distribution of the form p (x) = exp (- | x |), the mean absolute deviation is more informative than the standard deviation, but if its form is close to the normal, p (x) = exp (- x ^ 2), the standard deviation is more important. so whether to use the mean absolute or standard deviation depends on the distribution of the data. there is a field called robust statistics that looks at this question .
taleb’s books introduced me to seneca and stoicism and a whole area of a psychological biases that i hadn’t really spent much time considering or thinking about beforehand or reading. other books cover these areas better. for stoicism, actually reading seneca’s letters or marcus aurelius’s meditations is better than reading taleb’s version of it. for psychological biases, actually reading daniel kahneman is better than reading taleb. it sounds like in the areas where you agree with taleb with finance or math, you think a person would gain better understanding elsewhere .
the central limit theorem shows us that unimodal data with lots of independent sources of error tends towards a normal distribution. that description is a good first - pass, descriptive model for lots and lots of contexts, and standard deviation speaks well to normally distributed data .
i just have a simple question for taleb’s defenders. i’d love to know where he has offered more than the following two ideas :
aug. 16 — nassim nicholas taleb, adviser at universa investments, sat down for an interview with erik schatzker tuesday evening in new york. taleb, famous for his assessment of risk, says there are greater risks out there than nuclear war with north korea .
the holy grail distribution has a positive mean to justify the instrument' s permanent role in the asset allocation framework. its positive fat tail, which is
co - located
with the left tail of other instruments, adds protection to investment portfolios during tail risk events .
odd enough. i think he’s smeared buffet and charlie munger as “lucky” before, though i may be confusing taleb with burton malkiel here .
this article is based on paper taleb published in 2007. if you want to test yourself, submit yourself to experiment in page 3 :
key point number one in this memo is that the future should be viewed not as a fixed outcome that’s destined to happen and capable of being predicted, but as a range of possibilities and, hopefully on the basis of insight into their respective likelihoods, as a probability distribution .
i don’t have a problem with your comments about taleb, because he’s never interested me enough to pay attention to what he has to say .
taleb the philosopher observes that when it comes to the preservation and perpetuation of life, negative advice is more useful – the thou shalt nots .
your post was in reply to someone asking about taleb' s black swans so i assumed you were talking about 2008 in reference to that .
nassim nicholas taleb, fooled by randomness: the hidden role of chance in the markets and in life, new york: texere, 2001 .
this is hardly a matter of trust, anton. scott has pointed you in the direction of the relevant academic literature as regards taleb’s revival of the long - shot lure. and if you want to know what an expert in extreme value theory thinks of taleb, you can read this :
of course taleb would not offer a useful alternative. he says repeatedly that there is no useful alternative. throw them all away! !! !
i just came across this taleb interview made in february 2008, about taleb’s view on simons. taleb says verbatim answering the 4th question (about buffet): .. the only two people i think who are not lucky; there is soros and then there is the other gentleman from renaissance. simons, he is not lucky. he is beyond. there is no exposure to uncertainty on his models. ” the video is here: urltoken
that' s not interesting? i think the difference between theory and practice is intensely interesting, and taleb has a lot to say about it .
no. it is the ideology of dissing taleb. obviously i am not his paid spokesperson. but please argue to the merit of his arguments .
more interesting will be how the fda takes into account the arguments that taleb and co put forward. expect fireworks in the coming weeks and months .
many economists and, by direct extension, financiers thought they had quantified all forms of risk. by quantifying all forms of risk, you can compute the first derivative. taleb and scores of others argued that all risk cannot be quantified. taleb made this argument long before the publication of black swan .
ahhh taleb… you got to hand it to taleb, he has a huge head for heights, but has he really got those “street smarts” he so oft speaks of? its quite obvious that the success of dynamic hedging had an funny (ha) effect on him. barking mad? definately maybe .
what about bank’s debt converted into equity? ?! !! this was after all the quantitative easing, only taleb transferred the concept to individual consumers .
maybe taleb is in fact the genius he sets out to prove himself to be. after all, he did come up with a seemingly valid formula :
for the most part, taleb criticizes everything but he never offers any solutions. his observations when they make sense are trivial, like tails are fat .
[ … ] scott locklin on nassim nicholas taleb. akpc _ ids + =
126 ,
; popularity: unranked [? ] [ … ]
actually, taleb has explicitly stated that the 2008 financial crisis was not a black swan nor does he claim to be able to predict any of them .
it is sad that taleb does not see the value in the standard deviation; standard deviation is far more natural, and more useful, than mad .
still, i think that non - parametric methods are much more valuable as a solution to dealing with non - normal data than what taleb is proposing .
> the problem of course is that the cauchy distribution is pathological in that it doesn' t have a mean or variance, you can calculate similar properties for it (location and scale), but it doesn' t obey the central limit theorem so in practice it can be very strange to work with .
a key difference between these types of risks is the statistical structure of their impact. this structure is either dependent on scale or independent of scale. an example of a scale - dependent distribution is the weight of an adult human which is generally never greater than about 10 times the weight of an average human .
also he alludes to his paper with goldstein. it is clear form goldstein and taleb' s manuscript that that taleb is not just throwing these arguments to talk trash about practitioners of statistics. they report findings of an experiment with multiple groups of applied statisticians. i' ll quote from it [ 1 ] :
another solution to the problem of hedging tail risk events is to have a complementary strategy with a performance pattern that helps reduce the impact of market performance shocks. an instrument with a returns distribution featuring a positive mean and a fat, right (positive) tail that is realized just when traditional portfolios take a hit .
the black swan book? really, it’s like taleb found a way to fill his publisher’s ink cartridges with crap before having the manuscript sent to the printers .
excellent! another entertaining piece of fiction. much shorter than the first, but since i’m a complete unknown and taleb is well - known that’s only appropriate .
there is no snark in my post: i am outright calling taleb a false prophet who is guilty of exactly the things he criticizes in fooled by randomness .
by the way, i studied some stock rates to see taleb' s arguments, a thing i normally wouldn' t do. see my blog above .
tagged with black swans, delta hedging, implied volatility, nassim taleb, nickels in front of a steamroller, options, vix, volatility, volatility arbitrage .
i don’t think the essential criticism is that taleb is hysterical. (his hysteria may be a marketing tactic). i read the argument as: taleb affirms quantitative nihilism. (i am not myself sure, i just read that as the argument. like i said, i am here for the writing clinic…) .
and you are basing that statement on…. hahahaah! please enlight us on your specific sources of how you know that and why taleb is lying about his profession .
i am yet to see anybody who thinks that standard deviation is mean deviation. it' s taleb though. baseless assertions insulting groups of people are his craft .
gladwell plays into the comparison about as much as the editors of cosmopolitan would play into it if niederhoffer and taleb had shared the cover of an issue of cosmo .
[ … ] nassim taleb: clown of quantitative finance « locklin on science – as such, taleb is merely setting himself up as some sort of heretical alpha monkey of the quants for stating the obvious, the misleading, and occasionally the gratuitously wrong - headed and untrue. – lol heretical alpha monkey of the quants [ … ]
i hold bush responsible for all of this…taleb’s book is entertaining. where is the book from india that talked about reddy adn his ideas. that’s the book we needed .
< plus, it’s not like jim simons has time to write financial times < articles. he’s too busy making money more or less proving people like < taleb wrong .
taleb did not claim the banking crash to be a black swan (unpredictable). it was completely predictable and he has said as much. you probably overlooked that .
i’m having a tough time deciding which is right on this, you or taleb. could you please tell me your net worth so i can compare it to his ?
i will say though, taleb reader' s are surely great words with friends or scrabble players. you just can' t help picking up a few new words .
i am wondering if you have a lot invested in concepts and techniques that mr taleb is suggesting are broken. there is certainly a tone of defensiveness about your post .
rely on predictions of events that are unpredictable - so faulting him for predicting or not predicting this and that means one does not really understands what taleb is talking about .
he is saying it' s not useful for real world things and people are just confused. what you wrote is reasonable view. what taleb writes isn' t .
the true hero is not taleb, but reddy, the master of india’s banks, who kept sanity during an insane time. india and china are doing fine, thanks very much, due to their restraint and maturity. taleb’s point is simply to identify the flaw in quant models that kept regulation from doing its job in the last decade .
i think that taleb is extremely interesting. well, maybe not taleb himself, but the phenomenon of taleb. post the crisis, he’s such a great example of everything he criticised pre the crisis, one wonders whether anyone in the audience at his popular lectures ever reflects on this contradiction. rare events: before the fact, hard to predict; after the fact, easy to explain. but how ingenious to be able to sell this insight whilst simultaneously declaring that one predicted a rare event, and explaining how ?
good to see an fairly anti - taleb post picking actual holes in what he says – as someone who is definitely pro - taleb (his books have changed my outlook on various aspects of life) i have often tried to find holes in his logic and never have been able to – i am not convinced this post changes that but definitely got me thinking and one of the few anti - taleb posts (well at least not fawningly positive) that doesnt really resort to playing the man instead of the ideas .
yes, and capm is based on the gaussian also, as is most everything in first year quantitative finance. that doesn’t make these models useless any more than other statistical models based on gaussians when we know the process ain’t normal. hell, the entire concept of “statistical distribution” itself is kind of a lie: everyone knows financial processes are markov .
the most popular pop - writer in quantitative finance at present is nassim taleb. his latest screed in the financial times is what spurred me to write this post. the article wasn’t entirely written by taleb - though i guess the other guy is his fund partner, so it is no surprise that it suffers from all the mush headed absurdity of taleb’s other articles and books. i won’t pick on the other guy; or even mention his name: he’s got a job to do, and he has the good manners to not make himself a public figure. taleb, on the other hand, is sort of the paul feyerabend of quantitative finance. like feyerabend, he is well read, a good writer and quite charming. like feyerabend, taleb seems to earn his daily bread by showing up and being kind of witty. finally, both feyerabend and taleb are very much against method. this means, effectively, they’re both intellectual nihilists. feyerabend thought we couldn’t know anything for various reasons too silly to get into right now. taleb thinks all of quantitative finance is nonsense and we should do away with quants. i am guessing the former’s delusions had something to do with drinking the same berkeley tapwater in the 1960s which made everyone else believe in crazy things, but taleb was a trader, and it’s a common prejudice of traders to dislike quants for cutting into their p / l .
if you want to make that argument, then you need to look at popper. indeed, taleb’s writing and logic are much closer to popper than any of the relativists .
the problem that taleb is generally referring to in financial models (and those are the published models, not proprietary models) is that they use statistical concepts founded from physics .
i don' t agree with your' vile idiot' statement but i mostly concur with your thoughts. i hope that you don' t let taleb affect your senescence .
the appeal of any popular mountebank is best summed up by p. t. barnum: there is one born every minute. had taleb been an honest writer, he might have educated his readers on the concept of “sample bias. ” but if taleb were an honest writer, nobody would read his stuff. smugness is a lot cheaper than understanding .
i guess i share taleb' s problems with models. even before i read taleb i would say to myself
the map is not the territory
, particularly with regard to software abstractions. i think the space between the model and reality is where you find a lot of interesting things (including the ability to make a lot of money) .
second, in regard to conglac2009’s (michael’s) comment, taleb shouldn’t be requiring, or expecting, ft readers to read his prior books before reading an op - ed piece .
here' s taleb on mandelbrot :
[ he ] had perhaps more cumulative influence than any other single scientist in history, with the only close second, isaac newton .
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over the past few months i’ve been forming a thesis about where the world is heading. much of my thinking comes from seven important books. two of the most important authors who have influenced my thinking are nassim nicholas taleb and jaron lanier. many of the ideas that follow are theirs. and when taleb’s and lanier’s ideas intersect, you get very interesting hypotheses .
“taleb thinks all of quantitative finance is nonsense and we should do away with quants. i am guessing the former’s delusions had something to do with drinking the same berkeley tapwater in the 1960s which made everyone else believe in crazy things, but taleb was a trader, and it’s a common prejudice of traders to dislike quants for cutting into their p / l. ”
yeah, i could make up a whole story “filling in the blanks” about how taleb actually is the clever monkey he says he is. or i could make up a whole story “filling in the blanks” of how we’re not in an economic crisis. or i could just concentrate on what taleb actually said in both his books, essays and his wacky financial times article .
“non - normality is why i’ve made myself a minor expert in kernel regression. if i had listened to taleb, i’d have thrown up my hands and gone back to physics. ”
“there are far more successful and long lived funds, as i have already pointed out which trade the inverse of the taleb “swan strategy” at very high sharpe ratios. ” – scott locklin
scott locklin can be peer reviewed right here on the internet, sparky. i don’t get paid to make fun of taleb for a living: though it sounds like a fun job .
i really tried to get through
the black swan
and taleb' s writing struck me as so pretentious and self - involved that it made it impossible for me to finish .
i actually love taleb' s books (black swan, antifragile). and i work with
data scientists
, most with ph. d. s, many in statistics .
you' re late! taleb began publishing his arguments years ago and continues to publish. you' re way behind. read his papers and read his books in the following order :
i was a senior quant at renaissance (simons' outfit) working on options among other things. what' s annoying about taleb is the overtones that every one else in the business is a moron. does he really think that simons believes market moves are normally distributed? indeed i wrote a paper internal to renaissance on the distribution of tail area moves. taleb seems to think that these can' t be modeled, but i have never understood his reasons for thinking that. there is a whole area of statistics (
extreme value theory
) which seemed to me to apply well to financial data. our data in renaissance yielded quite good models, which i' ve no reason to think have broken down with the market crash .
« the world has lost trillions » the world has made and then lost trillions of paper gains and then losses. « through the hands of risk managers and courtesy their models based on gaussian distribution and other quantitative techniques. » courtesy of their using whatever mathematical technique looked likely to underestimate risks and lead to higher papers profits and cash bonuses by requiring less than prudential reserves .
once we' ve considered that little exercise above, we can almost deduce what taleb distribution is. it describes a situation that has very steady, consistent gains but has a hugely skewed risk / reward profile. so we can transfer this idea to trading forex, for the purpose of any calculations we will assume that the round trip cost of trading eurusd equates to 1 pip after commissions - of course this will vary with market liquidity. this strategy is commonly employed by major hedge funds and is commonly referred to as
picking pennies up ahead of a steamroller
nassim taleb criticized pinker’s arguments a few years ago, arguing that pinker didn’t take proper account of the statistical nature of war as a historical phenomenon, specifically as a time series of events characterized by fat tails. such processes naturally have long periods of quiescence, which get ripped apart by tumultuous upheavals, and they lure the mind into mistaken interpretations. pinker responded, clarifying his view, and the quotes above come from that response. pinker acknowledged the logical possibility of taleb’s view, but suggested that taleb had “no evidence that is true, or even plausible. ”
it' s a useful metric when treated carefully, but it is rare to encounter it treated carefully. science courses would be well - served to stop teaching it in favor of a stronger emphasis on multiple distributions. (multiple distributions are usually touched upon, but implicitly our curricula overfavor the gaussian distribution and end up accidentally implicitly convincing students its the only one. )
this has nothing to do with taleb and everything to do with genuine intellectual inquiry. if academics were thinkers rather than followers, it would be possible to prevent the gross abuse of paradigms .
author of' the black swan' and' fooled by randomness' former trader nassim nicholas taleb illustrates the concept of the' barbell strategy' - a risk hedging strategy robust to losses .
assume these experiences were drawn from the bell - shaped normal distribution on which such claims are generally based. if i were to write down as a percentage the probability that goldman sachs would encounter three 25 standard deviation events followed by a 20 standard deviation event, the next 15 lines of this column would be occupied by zeros. such things simply do not occur. so what did ?
people have a natural bias to look at returns and not to look at possible losses ,
says taleb .
if you reduce big losses, your overall returns will be higher .
however, taleb is not a relativist nor is he logical positivist, which is what most economics faculty are. he is a falsificationist. in my limited experience, most research methodologists are falsificationists .
i also agree with taleb that ducks are occasionally black and that water is generall wet. that doesn’t make the rest of what he says less idiotic. go back and read what i wrote .
[ … ] had thought that truly great polemic was dead and gone. i was wrong. it’s directed at nassim taleb, the black swan guy and here’s a sample: mountebanks [ … ]
like taleb, you remain unable to name one of them models, or suggest a useful alternative. stating that “models sometimes don’t work” is as useful as “sometimes boats sink. ” stating where they don’t work, why, and how to fix them is useful. taleb is not useful, relevant or even much of anything beyond a third rate charlatan who impresses the rubes with big words .
a central challenge of strategy is that we have to make choices now, but the payoffs occur in a future environment we cannot fully know or control. a critical step in embracing uncertainty is to try to characterize exactly what variety of it you face—a surprisingly rare activity at many companies. our work over the years has emphasized four levels of uncertainty. level one offers a reasonably clear view of the future: a range of outcomes tight enough to support a firm decision. at level two, there are a number of identifiable outcomes for which a company should prepare. at level three, the possible outcomes are represented not by a set of points but by a range that can be understood as a probability distribution. level four features total ambiguity, where even the distribution of outcomes is unknown .
on sept. 10, 2009 former trader and bestselling author nassim taleb did something that he very seldom does: he wore a tie. taleb has oftentimes publicly expressed his distaste for the blood - constraining artifacts, as well as for those who tend to don them, so the lebanese - american let the world know that was a very special day for him by betraying a sacred personal disposition .
[ … ] 21, 2009 scott locklin dismisses taleb in a recent post. i won’t get into the quant debate, as i’m not qualified to judge, but i will pick up [ … ]
while i am not a taleb fan (he had his own black swan and became exactly the reviled expert his own books warn us about), your hostility in this case seems out of place .
description: author of' the black swan' and' fooled by randomness' former trader nassim nicholas taleb illustrates the concept of the' barbell strategy' - a risk hedging strategy robust to losses .
if you are scratching your head in utter confusion, do not worry. i will continue to delve into this topic with examples and pictures so that we can all grasp the basics. the general idea for the strategy is that options inherently trade at an implied volatility that is higher than realized volatility on average. some academics (nassim taleb) believe that options trade at a higher implied volatility because black - scholes assumes a normal, bell shaped, distribution in stock returns. we can all agree that stock returns are anything but normal after going through the extreme volatility of 2008. in fact, during the 4th quarter of 2008 the s & p 500 had moves in excess of + / - 5% during 25% of the trading days. if we assume that the s & p 500 has a long - term standard deviation of 20% on average, then a 5% daily move is in excess of 4 standard deviations. in a nutshell, equity markets are fat - tailed, meaning that observations that are far away from the mean happen much more frequently than a normal distribution can account for. nassim taleb would argue that these “black swan” events more than wipe out the small profits from selling options .
another problematic example comes from taleb’s disdain for mathematics in economics. he has misstated his case. a minority of economics, finance, and marketing faculty believe that economics has become nothing more than calculus. taleb’s disdain comes from falsificationists’ philosophy. there are two types of theories: theories that have been disproved (e. g. , newtonian physics) and theories that cannot be disproved given current research methods .
funny, i’m pretty sure the sharpe ratio does pretty well at noticing that taleb’s fund is a massive pile of suck. feel free to pick any other performance metric: yearly returns, cumulative returns, sortino ratio, bias ratio; doesn’t matter: his fund still amounts to “capital assets destruction model. ” wheras betting against taleb’s dumb strat is a good business, and tail risks can apparently be managed .
> taleb doesn' t point one situation when mad works better than sd (i pointed out some where sd works better than mad) he also doesn' t address obvious problems which such substitutions create .
you state that
standard deviation tells you how volatile measurements are
. but taleb shows how financial markets are non - gaussian and have
fat tails
and gives the data and the supporting arguments .
though, i do not fully agree to the second part of your analysis as i think you miss taleb’s point. – a black swan event is by definition unexpected. the best we can do is hedge against those events. when taleb says one shall be long on options, it is only a matter of the capped loss they provide (even if the payoff may be lower than selling options). you may make less money than in shorting implied volatility, but you are hedged against a potential black swan. you’re saying taleb being wrong does not make sense at that particular point, as you’re target is different .
for nearly more than 50 years, going back to lewis fry richardson, it’s been known that the cumulative distribution of wars by size follows a rough power law, the number of events larger than size s being proportional to 1 / s raised to an exponent α. this is also an approximation, of course, because there is an absolute maximum possible size for a conflict — it can’t be more than then entire population. hence, the power law form can only hold over a certain range. to take this into account, cirillo and taleb also rescale the data to take into account the finite size of the human population.
in economics and finance , a taleb distribution is the statistical profile of an investment which normally provides a payoff of small positive returns , while carrying a small but significant risk of catastrophic losses . the term was coined by journalist martin wolf and economist john kay to describe investments with a " high probability of a modest gain and a low probability of huge losses in any period . " the concept is named after nassim nicholas taleb , based on ideas outlined in his fooled by randomness . according to taleb in silent risk , the term should be called " payoff " to reflect the importance of the payoff function of the underlying probability distribution , rather than the distribution itself . the term is meant to refer to an investment returns profile in which there is a high probability of a small gain , and a small probability of a very large loss , which more than outweighs the gains . in these situations the expected value is very much less than zero , but this fact is camouflaged by the appearance of low risk and steady returns . it is a combination of kurtosis risk and skewness risk : overall returns are dominated by extreme events ( kurtosis ) , which are to the downside ( skew ) . more detailed and formal discussion of the bets on small probability events is in the academic essay by taleb , called " why did the crisis of 2008 happen ? " and in the 2004 paper in the journal of behavioral finance called " why do we prefer asymmetric payoffs ? " in which he writes " agents risking other people ’s capital would have the incentive to camouflage the properties by showing a steady income . intuitively , hedge funds are paid on an annual basis while disasters happen every four or five years , for example . the fund manager does not repay his incentive fee . " 
in economics and finance, a taleb distribution is the statistical profile of an investment which normally provides a payoff of small positive returns, while carrying a small but significant risk of catastrophic losses. the term was coined by journalist martin wolf and economist john kay to describe investments with a " high probability of a modest gain and a low probability of huge losses in any period. " the concept is named after nassim nicholas taleb, based on ideas outlined in his fooled by randomness. according to taleb in silent risk, the term should be called " payoff " to reflect the importance of the payoff function of the underlying probability distribution, rather than the distribution itself. the term is meant to refer to an investment returns profile in which there is a high probability of a small gain, and a small probability of a very large loss, which more than outweighs the gains. in these situations the expected value is very much less than zero, but this fact is camouflaged by the appearance of low risk and steady returns. it is a combination of kurtosis risk and skewness risk: overall returns are dominated by extreme events (kurtosis), which are to the downside (skew). more detailed and formal discussion of the bets on small probability events is in the academic essay by taleb, called " why did the crisis of 2008 happen? " and in the 2004 paper in the journal of behavioral finance called " why do we prefer asymmetric payoffs? " in which he writes " agents risking other people ’s capital would have the incentive to camouflage the properties by showing a steady income. intuitively, hedge funds are paid on an annual basis while disasters happen every four or five years, for example. the fund manager does not repay his incentive fee. "
in economics and finance, a taleb distribution is the statistical profile of an investment which normally provides a payoff of small positive returns, while carrying a small but significant risk of catastrophic losses. the term was coined by journalist martin wolf and economist john kay to describe investments with a " high probability of a modest gain and a low probability of huge losses in any period. " the concept is named after nassim nicholas taleb, based on ideas outlined in his fooled by randomness. according to taleb in silent risk, the term should be called " payoff " to reflect the importance of the payoff function of the underlying probability distribution, rather than the distribution itself. the term is meant to refer to an investment returns profile in which there is a high probability of a small gain, and a small probability of a very large loss, which more than outweighs the gains. in these situations the expected value is very much less than zero, but this fact is camouflaged by the appearance of low risk and steady returns. it is a combination of kurtosis risk and skewness risk: overall returns are dominated by extreme events (kurtosis), which are to the downside (skew). more detailed and formal discussion of the bets on small probability events is in the academic essay by taleb, called " why did the crisis of 2008 happen? " and in the 2004 paper in the journal of behavioral finance called " why do we prefer asymmetric payoffs? " in which he writes " agents risking other people ’s capital would have the incentive to camouflage the properties by showing a steady income. intuitively, hedge funds are paid on an annual basis while disasters happen every four or five years, for example. the fund manager does not repay his incentive fee. "