Quote
Nassim Taleb on the black swans of war
Yahoo Finance By Justine Underhill
As the frequency of wars among great powers dwindles, has the world entered a new paradigm of peace and prosperity? Not quite, says Nassim Taleb, author of Fooled by Randomness and The Black Swan.
In their new paper, statistician Pasquale Cirillo and Taleb examine wartime events of the last 2000 years, and they find no statistical evidence that the frequency or magnitude of wars are declining. The "long peace" theory, which claims that violence has declined, is a falsehood says Taleb. He notes that people are lulled into a false sense of security because of the nature of so-called fat tail – or extreme – events.
"You cannot make claims that violence has dropped," he says. "Simply because, under fat tails, events can take hundreds of years. Large events can take a long time...and between events is totally unpredictable...they occur randomly with no time structure, and we saw no evidence of decline."
They also find that catastrophically fatal wars have fatter tails than those of financial crises, which suggests a propensity for extremes. Taleb notes that the severe cases of war are more deleterious than those of finance.
"It's much worse in the sense that a smaller number of events determine a larger share of the casualties," he says.
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Taleb adds that the role of randomness is misunderstood. He explains that using a past average to forecast a future average leads to a considerable underestimation of the number of casualties.
Regarding the role of statistical tools, Taleb says, “Physicists get the point. But social scientists do not get it. Their statistical tools do not work for what we call fat tails, as defined as something prone to black swan events," he says. "They can write whatever narrative they want. But we call that journalistic. That's not statistical."
Taleb clarifies the point, as he says, "If someone tells you violence has dropped and shows you fifty years of data, just laugh at the person. That's what we're saying."
video at link: http://finance.yahoo.com/news/nassim-taleb-on-the-black-swans-of-war-194841536.html (http://finance.yahoo.com/news/nassim-taleb-on-the-black-swans-of-war-194841536.html)
Complete bullshit.
Seems like doubletalk. They are correct to note that we don't know the "proper" time period for evaluating levels of violence, but, to paraphrase Taleb, "If a statistician tells you he has a better timeframe for determining random war events than you do, just laugh at the person."
Quote from: citizen k on May 19, 2015, 06:36:34 PM
Regarding the role of statistical tools, Taleb says, "Physicists get the point. But social scientists do not get it. Their statistical tools do not work for what we call fat tails, as defined as something prone to black swan events," he says.
The assumption here is that statisticians can only work with normal distributions which is false.
His book on black swans is interesting in that it provokes discussion and thought on "how do we plan for the unknown?", but he does get pretty obsessive. It's fun watching his rants on Youtube against economists.
Quote from: The Minsky Moment on May 19, 2015, 07:18:19 PM
Quote from: citizen k on May 19, 2015, 06:36:34 PM
Regarding the role of statistical tools, Taleb says, "Physicists get the point. But social scientists do not get it. Their statistical tools do not work for what we call fat tails, as defined as something prone to black swan events," he says.
The assumption here is that statisticians can only work with normal distributions which is false.
I think it's more that statisticians tend to discard outliers.
I think it's more that History and Poli Sci folks stop at intro to stats.
Not sure how fat tails changes the frequency. That's just a descriptor.
We're in the calm before the storm, folks. :ph34r:
Quote from: The Minsky Moment on May 19, 2015, 07:18:19 PM
Quote from: citizen k on May 19, 2015, 06:36:34 PM
Regarding the role of statistical tools, Taleb says, "Physicists get the point. But social scientists do not get it. Their statistical tools do not work for what we call fat tails, as defined as something prone to black swan events," he says.
The assumption here is that statisticians can only work with normal distributions which is false.
Yes and no. Obviously there are skewed distributions, but you may not have enough data to fit them accurately. The more skewed the distribution, the more data you need.
The murder rate has plunged in the last thousand years across most of the world. There hasn't been a major war in the Americas in a century and a half. There hasn't been a major war in Europe in seventy years. East Asia has been at peace for forty. It's ludicrous to argue that the world is not more peaceful than it used to be when everywhere in the world in 17th century looked like present day Syria.
Quote from: Admiral Yi on May 19, 2015, 08:10:55 PM
Not sure how fat tails changes the frequency. That's just a descriptor.
Fat tail and frequency are directly related. The lower the underlying frequency of the event, the more skewed the distribution of the number of events is (i.e. the more fat-tailed it is).
Quote from: jimmy olsen on May 19, 2015, 08:35:20 PM
The murder rate has plunged in the last thousand years across most of the world. There hasn't been a major war in the Americas in a century and a half. There hasn't been a major war in Europe in seventy years. East Asia has been at peace for forty. It's ludicrous to argue that the world is not more peaceful than it used to be when everywhere in the world in 17th century looked like present day Syria.
It's ludicrous to argue by just repeating the very point being refuted. Taleb's point is that wars may be distributed in such a way that we simply have no way of knowing whether expected losses from wars became less likely over the last 7 decades. Is he right? I don't know, that depends on whether he got his numbers right. Is it conceivable that he's right? Most definitely.
Quote from: DGuller on May 19, 2015, 08:46:08 PM
Fat tail and frequency are directly related. The lower the underlying frequency of the event, the more skewed the distribution of the number of events is (i.e. the more fat-tailed it is).
I was talking about this part.
"In their new paper, statistician Pasquale Cirillo and Taleb examine wartime events of the last 2000 years, and
they find no statistical evidence that the frequency ... of wars [is] declining. "
Surely that's just a counting and dividing operation.
Quote from: Admiral Yi on May 19, 2015, 08:56:21 PM
Quote from: DGuller on May 19, 2015, 08:46:08 PM
Fat tail and frequency are directly related. The lower the underlying frequency of the event, the more skewed the distribution of the number of events is (i.e. the more fat-tailed it is).
I was talking about this part.
"In their new paper, statistician Pasquale Cirillo and Taleb examine wartime events of the last 2000 years, and they find no statistical evidence that the frequency ... of wars [is] declining. "
Surely that's just a counting and dividing operation.
:bleeding: :frusty:
"Surely"? So what is it that you think statisticians do that arithmeticians can't do? No, there is a hell of a lot more involved than just counting and dividing. Counting and dividing just gives you the estimate. The important part of statistical analysis, the one embedded in "statistical evidence" part, is calculating the confidence interval around the counted and divided number. And the confidence interval is most surely a function of how fat the tail is.
It's occasionally interesting when we have someone who actually knows what the fuck they are talking about.
No need to be a dick Guller.
Quote from: Admiral Yi on May 19, 2015, 09:41:37 PM
No need to be a dick Guller.
Too harsh? Yes, in hindsight. It was the "surely" that pushed the button.
You also did not consider the possibility that "are declining" can be interpreted in a number of different ways.
Quote from: Admiral Yi on May 19, 2015, 10:31:18 PM
You also did not consider the possibility that "are declining" can be interpreted in a number of different ways.
It shouldn't be interpreted in a number of different ways. There is just one correct interpretation of the statement you bolded (regardless of the truth value of that statement).
Kinda seems like predicting the outliers is more or less the point of insurance statistics. Sociologists and the like are more interested in broader trends, so ignoring them makes their work more applicable, at least in the short run. But the outliers usually have a bigger impact than the rest for good and ill.
You can't figure out who's going to win an election by counting outliers. But if you could predict an outlier like a tsunami, the impact of that one data point would be much much more impactful to the world.
Quote from: MadImmortalMan on May 19, 2015, 10:46:57 PM
Kinda seems like predicting the outliers is more or less the point of insurance statistics. Sociologists and the like are more interested in broader trends, so ignoring them makes their work more applicable, at least in the short run. But the outliers usually have a bigger impact than the rest for good and ill.
You can't figure out who's going to win an election by counting outliers. But if you could predict an outlier like a tsunami, the impact of that one data point would be much much more impactful to the world.
No one predicts outliers. Statistics is not fortune-telling. I don't predict that John Doe will have a car accident on January 17th, 2016, or that a category 5 hurricane will make a landfall on Miami in 2018. That's pure fiction, you need to be able to explain variance many orders of magnitude better than what is currently possible for that to be even remotely realistic.
All statististicians just try to come up with probabilities, as precise as the data will allow them. The difference between good and bad statisticians is that good ones don't overstate the precision that their data allows them. Outliers are one of the variables that determine how much precision your data allows you, so ignoring them makes you overstate the precision, and thus makes you a bad statistician.
We're not trying to predict anything here, we're analyzing the past. Wars happened, or they didn't. People were killed or they weren't. Seems like simple arithmetic is appropriate for figuring out if wars and violence have declined over the last two thousand years.
Quote from: DGuller on May 19, 2015, 11:15:17 PM
Quote from: MadImmortalMan on May 19, 2015, 10:46:57 PM
Kinda seems like predicting the outliers is more or less the point of insurance statistics. Sociologists and the like are more interested in broader trends, so ignoring them makes their work more applicable, at least in the short run. But the outliers usually have a bigger impact than the rest for good and ill.
You can't figure out who's going to win an election by counting outliers. But if you could predict an outlier like a tsunami, the impact of that one data point would be much much more impactful to the world.
No one predicts outliers. Statistics is not fortune-telling. I don't predict that John Doe will have a car accident on January 17th, 2016, or that a category 5 hurricane will make a landfall on Miami in 2018. That's pure fiction, you need to be able to explain variance many orders of magnitude better than what is currently possible for that to be even remotely realistic.
All statististicians just try to come up with probabilities, as precise as the data will allow them. The difference between good and bad statisticians is that good ones don't overstate the precision that their data allows them. Outliers are one of the variables that determine how much precision your data allows you, so ignoring them makes you overstate the precision, and thus makes you a bad statistician.
I imagine in your business, the outliers are things like car crashes, house fires, crimes and stuff. Don't you guys at least try to budget for the claims?
Quote from: jimmy olsen on May 19, 2015, 11:28:56 PM
We're not trying to predict anything here, we're analyzing the past. Wars happened, or they didn't. People were killed or they weren't. Seems like simple arithmetic is appropriate for figuring out if wars and violence have declined over the last two thousand years.
No, we're trying to figure whether the world in the last 7 decades was an inherently more peaceful place, or whether it was just lucky. And we are in a way trying to predict something here, because by trying to suss out a trend, we're also trying to project what the environment will be like in the future.
Quote from: MadImmortalMan on May 19, 2015, 11:33:00 PM
I imagine in your business, the outliers are things like car crashes, house fires, crimes and stuff. Don't you guys at least try to budget for the claims?
All those things aren't really outliers. On an individual level, those are very rare events, but on aggregate the number of car crashes or house fires is quite predictable, since these events are uncorrelated, and you have a lot of policies. Budgeting for them is not that tricky.
The outliers, or rather black swan events, are large scale catastrophes like hurricanes or earthquakes, or worse yet, another kind of catastrophe that you can't even think of yet, but whose losses you still have to cover. There are catastrophe models out there, but the nature of fat-tail events is such that you can't ever truly know whether those are good or junk. How exactly do you test whether the model accurately predicts 1-in-1000 year hurricane events? All insurance companies accept a small risk that they'll just be shit out of luck sometimes.
I find the general premise that wars are random events questionable. The long peace theory is not based on mathematical or chronological considerations, but on alleged or perceived changes to human interaction in the last decades. As human interaction is not random, but based on will a pure mathematical analysis could fall short.
Guller lacks the confidence in his models to set up a small self-sustaining scientist colony in Greenland to weather the coming storm and lead our descendants back to civilization.
Quote from: Zanza on May 20, 2015, 12:36:25 AM
I find the general premise that wars are random events questionable. The long peace theory is not based on mathematical or chronological considerations, but on alleged or perceived changes to human interaction in the last decades. As human interaction is not random, but based on will a pure mathematical analysis could fall short.
Agreed. That's the problem with anyone looking at things from the standpoint of their profession; they assume they can answer the question using their professional tools. As the saying goes, "to the man with the hammer, all problems look like nails." Taleb's entire argument is premised on the assumption that wars are random events subject to statistical analysis. To paraphrase him again, "just laugh at the person."
Quote from: Zanza on May 20, 2015, 12:36:25 AM
I find the general premise that wars are random events questionable. The long peace theory is not based on mathematical or chronological considerations, but on alleged or perceived changes to human interaction in the last decades. As human interaction is not random, but based on will a pure mathematical analysis could fall short.
Actually there has been at least one statistical study that claimed death by violence has been on a long term decline, and I believe that there has been a similar one for war. You may not be using mathematical models, but other people have been.
Quote from: grumbler on May 20, 2015, 06:14:38 AM
Quote from: Zanza on May 20, 2015, 12:36:25 AM
I find the general premise that wars are random events questionable. The long peace theory is not based on mathematical or chronological considerations, but on alleged or perceived changes to human interaction in the last decades. As human interaction is not random, but based on will a pure mathematical analysis could fall short.
Agreed. That's the problem with anyone looking at things from the standpoint of their profession; they assume they can answer the question using their professional tools. As the saying goes, "to the man with the hammer, all problems look like nails." Taleb's entire argument is premised on the assumption that wars are random events subject to statistical analysis. To paraphrase him again, "just laugh at the person."
I think this criticism misses the mark as well. Statistics can be and is applied successfully to many events that are not truly random (if there even is such a thing as a truly random event). Car accidents are not truly random either, they're a result of two drivers' decisions that eventually made them occupy the same space at the same time. The key is whether the chain of events is so complex that the outcome is not truly predictable due to butterfly effects except in extremely short time horizons.
It's been a long morning, and I maybe can't really understand what Taleb is saying.
So correct me if I am wrong: the fact that conflict and violence has measurably been decreasing doesn't make the world 'a more peaceful place' because the substantial possibility remains of a future, highly destructive conflict tied in some way to past and/or current events?
Maybe I am just too soaked in the assumptions of my field of conflict studies, but I am struggling to think of anyone working in foreign affairs or international security that
doesn't know this to be true - even those of us who have read Pinker's work and taken it on board. Anyone aware of the existence of nuclear weapons, for instance, will know that conflict - a single conflict event - has the potential to wipe out in minutes what the Second World War took six years to do. Anyone watching Ukraine over the last two years, as an other example, will have an instinctive appreciation for the dangerously destabilising effect a seemingly self-contained civil political dispute can have on military security of an entire continent.
And like others have suggested in this thread already, other variables have an important impact on the incidence of war and violence, on which a lot of work has been done.
It seems to me, again I could be wrong, that Taleb and his co-author are using statistical theory to make a dubious point that we cannot consider the world peaceful because of the potential impact of a potential conflict. I think this mixes up 'peaceful' with 'stable'. The world in 1913 was peaceful; but it was not stable.
The TL;DR version - they're playing Languish-semantics because they don't like Stephen Pinker's book
Also:
QuoteRegarding the role of statistical tools, Taleb says, "Physicists get the point. But social scientists do not get it. Their statistical tools do not work for what we call fat tails, as defined as something prone to black swan events," he says. "They can write whatever narrative they want. But we call that journalistic. That's not statistical."
Is it really the case that someone so intelligence as Taleb could fail to realise that modelling human behaviour, particularly historical human behaviour with scant or unreliable data sources, is not at all like modelling physical systems?
Quote from: Zanza on May 20, 2015, 12:36:25 AM
I find the general premise that wars are random events questionable. The long peace theory is not based on mathematical or chronological considerations, but on alleged or perceived changes to human interaction in the last decades. As human interaction is not random, but based on will a pure mathematical analysis could fall short.
I can't think of any quantitative political scientists that model wars as random events.
Here's my take on what he's saying:
History doesn't have nice, evenly distributed wars of average magnitude. Things can go peacefully for a while the all hell breaks loose. So the fact that we're in a peaceful stretch right now doesn't necessarily mean that the underlying distribution has changed.
Which, as an aside, is not at all the same thing as saying the frequency and magnitude of war are exactly the same now as they have always been.
Quote from: Warspite on May 20, 2015, 09:23:32 AM
So correct me if I am wrong: the fact that conflict and violence has measurably been decreasing
Let's stop right here. The bolded assertion is what is being challenged. Taleb's argument is that wars are so statistically volatile that it is not statistically supportable to claim that war frequency has measurably been decreasing. He's not saying that it's increasing or staying the same, he's just saying that you can't tell with the data we have, if you properly account for the historical volatility of war frequencies.
Quote from: Admiral Yi on May 20, 2015, 09:28:38 AM
Here's my take on what he's saying:
History doesn't have nice, evenly distributed wars of average magnitude. Things can go peacefully for a while the all hell breaks loose. So the fact that we're in a peaceful stretch right now doesn't necessarily mean that the underlying distribution has changed.
Which, as an aside, is not at all the same thing as saying the frequency and magnitude of war are exactly the same now as they have always been.
This is exactly right.
Quote from: DGuller on May 20, 2015, 09:31:53 AM
Quote from: Warspite on May 20, 2015, 09:23:32 AM
So correct me if I am wrong: the fact that conflict and violence has measurably been decreasing
Let's stop right here. The bolded assertion is what is being challenged. Taleb's argument is that wars are so statistically volatile that it is not statistically supportable to claim that war frequency has measurably been decreasing. He's not saying that it's increasing or staying the same, he's just saying that you can't tell with the data we have, if you properly account for the historical volatility of war frequencies.
Ok. Then we need to see how Taleb codes "war" because what has been considered under the label "war" has a huge impact on how violent the world seems.
As a practical example: consider that measures of violent death in El Salvador did not decrease after the signing of the Chapultepec peace accord; on the contrary, they even increased. Yet the "war" was considered to have stopped; the event was finished. Other highly violent societies slip in and out of "war" based on reasons of political labeling, not underlying reality.
What Pinker's work tried to show was that stripping away the labels the world has been becoming less violent - and thus more peaceful.
Quote from: DGuller on May 20, 2015, 08:09:54 AM
I think this criticism misses the mark as well. Statistics can be and is applied successfully to many events that are not truly random (if there even is such a thing as a truly random event). Car accidents are not truly random either, they're a result of two drivers' decisions that eventually made them occupy the same space at the same time. The key is whether the chain of events is so complex that the outcome is not truly predictable due to butterfly effects except in extremely short time horizons.
Okay, I can see I overstated the "random" element, but the argument that, even if wars are demonstrably less frequent over the last 70 years, such evidence is meaningless because of the "fat tail" of a distribution still implies an element of randomness.
Quote from: grumbler on May 20, 2015, 09:42:12 AM
Okay, I can see I overstated the "random" element, but the argument that, even if wars are demonstrably less frequent over the last 70 years, such evidence is meaningless because of the "fat tail" of a distribution still implies an element of randomness.
Taleb quotes this research, but it is a useful example.
The Physical Limits of Trick Shots in Billiards (http://io9.com/the-physical-limit-of-trick-shots-in-billiards-1532036405)
QuoteThe joker in the deck is gravity, a force that no one can entirely "screen out," no matter where they are in the universe. It makes a difference in the path of molecules and the path of billiard balls. For the first collision of a billiard ball, we can control the variable so well that we don't really have to think of gravity as anything other than the force holding the ball on the table. We control all the variables that matter: the placement and force of the hit. After a couple of collisions, we're less able to determine where the balls go. Even on an idealized surface, there are many options depending on the exact force with which the balls meet, and the forces acting upon them. After six or seven collisions, you don't just have to worry about the gravity of the Earth, but of the gravity of the people walking around the table. Exactly where these people are, and the gravitational pull their mass exerts on the balls, will determine whether the balls go one way or another. This means that, unless a pool player can carefully weight the people around the table, determine where they stand, there's no possible way for anyone to be certain of the trajectory of a ball after six or more collisions.
The issue isn't the influence of randomness, it's the difficulty of computing an accurate result due to the amount of data needed. Determining the likelihood of war probably takes an amount of data and calculation that is well beyond any computer for the foreseeable future.
Some interesting initial debates are already happening on the blogosphere about this paper. See for instance:
http://wmbriggs.com/post/16012/
Quote from: DGuller on May 19, 2015, 08:19:47 PM
Quote from: The Minsky Moment on May 19, 2015, 07:18:19 PM
Quote from: citizen k on May 19, 2015, 06:36:34 PM
Regarding the role of statistical tools, Taleb says, "Physicists get the point. But social scientists do not get it. Their statistical tools do not work for what we call fat tails, as defined as something prone to black swan events," he says.
The assumption here is that statisticians can only work with normal distributions which is false.
Yes and no. Obviously there are skewed distributions, but you may not have enough data to fit them accurately. The more skewed the distribution, the more data you need.
There are statistical tools for dealing with non-normal distributions, including fat-tailed distributions. So Talib is just wrong. He didn't say normal distributions were more tractable, or easier to deal with, or cet. par. require less data to reach significant conclusions, all which would be justifiable. He said statistical tools "do not work," no qualification.
No Joan. He said *their* statistical tools don't work.
Quote from: Admiral Yi on May 20, 2015, 12:30:11 PM
No Joan. He said *their* statistical tools don't work.
Referring to all "social scientists" !
It's not like physicists have some magic set of statistical tools that no one else knows about or uses.
I have a massive tool.
I wish. :(
Quote from: The Minsky Moment on May 20, 2015, 12:33:35 PM
Quote from: Admiral Yi on May 20, 2015, 12:30:11 PM
No Joan. He said *their* statistical tools don't work.
Referring to all "social scientists" !
It's not like physicists have some magic set of statistical tools that no one else knows about or uses.
No, it's that the social scientists have a different goal, and excluding the outliers makes it more likely that their work will be useful. I don't think that's necessarily a criticism of their work. They're trying to find out things like who will win an election, not prepare for random events.
Someone had an incredibly large sig.
Quote from: MadImmortalMan on May 20, 2015, 04:36:47 PM
No, it's that the social scientists have a different goal, and excluding the outliers makes it more likely that their work will be useful. I don't think that's necessarily a criticism of their work. They're trying to find out things like who will win an election, not prepare for random events.
Social scientists is such a broad category that it makes so sense to say that. Some social scientists focus on outliers. Like for example, Talib. Who happens to be a social scientist.
Quote from: The Minsky Moment on May 20, 2015, 12:27:33 PM
There are statistical tools for dealing with non-normal distributions, including fat-tailed distributions. So Talib is just wrong. He didn't say normal distributions were more tractable, or easier to deal with, or cet. par. require less data to reach significant conclusions, all which would be justifiable. He said statistical tools "do not work," no qualification.
The key bit is "Their statistical tools". He's assuming (correctly in many situations) that they aren't using the tools that can deal with some non-normal distributions.
Quote from: frunk on May 20, 2015, 07:57:40 PM
Quote from: The Minsky Moment on May 20, 2015, 12:27:33 PM
There are statistical tools for dealing with non-normal distributions, including fat-tailed distributions. So Talib is just wrong. He didn't say normal distributions were more tractable, or easier to deal with, or cet. par. require less data to reach significant conclusions, all which would be justifiable. He said statistical tools "do not work," no qualification.
The key bit is "Their statistical tools". He's assuming (correctly in many situations) that they aren't using the tools that can deal with some non-normal distributions.
That was my interpretation as well, and I think Joan is reaching a little in his interpretation. If Taleb believes that there are no statistical tools to deal with fat tails, then my guess would be that he wouldn't publish a paper where he uses statistical tools that deal with fat tails.
Quote from: DGuller on May 20, 2015, 10:36:20 PM
Quote from: frunk on May 20, 2015, 07:57:40 PM
Quote from: The Minsky Moment on May 20, 2015, 12:27:33 PM
There are statistical tools for dealing with non-normal distributions, including fat-tailed distributions. So Talib is just wrong. He didn't say normal distributions were more tractable, or easier to deal with, or cet. par. require less data to reach significant conclusions, all which would be justifiable. He said statistical tools "do not work," no qualification.
The key bit is "Their statistical tools". He's assuming (correctly in many situations) that they aren't using the tools that can deal with some non-normal distributions.
That was my interpretation as well, and I think Joan is reaching a little in his interpretation. If Taleb believes that there are no statistical tools to deal with fat tails, then my guess would be that he wouldn't publish a paper where he uses statistical tools that deal with fat tails.
Well we can't really judge his interpretation easily because there's no literature review in the paper, and neither has the paper passed peer review yet.
EDIT: I sit on the editorial board of a journal - they wouldn't be the first two well known academics in their field to make grand pronouncements about the methodological rigour of another field and be completely wrong.
Quote from: frunk on May 20, 2015, 07:57:40 PM
The key bit is "Their statistical tools". He's assuming (correctly in many situations) that they aren't using the tools that can deal with some non-normal distributions.
:huh:
It's a pretty simple set of 2 English sentences.
"But social scientists do not get it. Their statistical tools do not work for what we call fat tails."
There is no qualification, no nuance, no explanation. He is singling out the entire category of social scientists and saying their methods don't work. Period.
Quote from: DGuller on May 20, 2015, 10:36:20 PM
If Taleb believes that there are no statistical tools to deal with fat tails, then my guess would be that he wouldn't publish a paper where he uses statistical tools that deal with fat tails.
Ah but that's the point isn't it? Taleb is the great iconoclastic genius who alone truly understands, who will save the masses from those misguided social scientists who can't grasp his brilliant insights. (unless they buy his most recent book . . on sale now!)
I easily lose patience with this kind of nonsense.
Quote from: The Minsky Moment on May 21, 2015, 10:19:09 AM
Quote from: DGuller on May 20, 2015, 10:36:20 PM
If Taleb believes that there are no statistical tools to deal with fat tails, then my guess would be that he wouldn't publish a paper where he uses statistical tools that deal with fat tails.
Ah but that's the point isn't it? Taleb is the great iconoclastic genius who alone truly understands, who will save the masses from those misguided social scientists who can't grasp his brilliant insights. (unless they buy his most recent book . . on sale now!)
I easily lose patience with this kind of nonsense.
:hmm: Sounds like you have prior issues with Taleb.
Don't know him, never met him, just read his stuff.
I'm embarrassed to admit it, but I've never read Fooled by Randomness. This thread finally made me go and order the book on Amazon, to see what he himself has to say.
That said, from what I know of the main argument that he has to make, his point is definitely one that needs to be made much more often. Maybe he's not the first one to realize that ignoring those rare outliers can completely invalidate your sophisticated-looking models, and embark you on a dangerous path as you make decisions with it, but he's definitely the first one to make the masses think about it.
DG I don't have a problem with that. I think popularization of ideas like that is a very good thing. But it ends up being counterproductive when it involves dubious sweeping unqualified claims, accuses everyone else in his field of being fools, and attacks everyone else's motivations.
Look at someone like Daniel Kahneman - that's a real bona fide genius, who really did come up with theoretical insights that demonstrated fundamental flaws in basic methods of a number of fields, did vast amounts of empirical work to verify and hone his theories, AND popularized it to boot. And yet managed not to be a arrogant prick about it.
I thought it was a trivial point Joan. The types of academics who look at things like declining warfullness trends don't usually get very far into statistics.
Being an arrogant prick seems to be a necessary trait for options traders. :P
Taleb only became an academic after he got rich.
Quote from: Admiral Yi on May 21, 2015, 10:51:03 AM
The types of academics who look at things like declining warfullness trends don't usually get very far into statistics.
Don't know if that is necessarily true, but if it is true, it only makes his much broader indictment even more gratuitous and unnecessary.