Enter your mobile number or email address below and we'll send you a link to download the free Kindle App. Then you can start reading Kindle books on your smartphone, tablet, or computer - no Kindle device required.
To get the free app, enter your mobile phone number.
Other Sellers on Amazon
+ $3.99 shipping
+ $3.99 shipping
+ $3.99 shipping
The Black Swan: Second Edition: The Impact of the Highly Improbable: With a new section: "On Robustness and Fragility" (Incerto) Paperback – May 11, 2010
|New from||Used from|
Featured business titles
Sponsored by McGraw-Hill Learn more.
Frequently bought together
Customers who bought this item also bought
Bestselling author Nassim Nicholas Taleb continues his exploration of randomness in his fascinating new book, The Black Swan, in which he examines the influence of highly improbable and unpredictable events that have massive impact. Engaging and enlightening, The Black Swan is a book that may change the way you think about the world, a book that Chris Anderson calls, "a delightful romp through history, economics, and the frailties of human nature." See Anderson's entire guest review below.
Guest Reviewer: Chris Anderson
Chris Anderson is editor-in-chief of Wired magazine and the author of The Long Tail: Why the Future of Business Is Selling Less of More.
Four hundred years ago, Francis Bacon warned that our minds are wired to deceive us. "Beware the fallacies into which undisciplined thinkers most easily fall--they are the real distorting prisms of human nature." Chief among them: "Assuming more order than exists in chaotic nature." Now consider the typical stock market report: "Today investors bid shares down out of concern over Iranian oil production." Sigh. We're still doing it.
Our brains are wired for narrative, not statistical uncertainty. And so we tell ourselves simple stories to explain complex thing we don't--and, most importantly, can't--know. The truth is that we have no idea why stock markets go up or down on any given day, and whatever reason we give is sure to be grossly simplified, if not flat out wrong.
Nassim Nicholas Taleb first made this argument in Fooled by Randomness, an engaging look at the history and reasons for our predilection for self-deception when it comes to statistics. Now, in The Black Swan: the Impact of the Highly Improbable, he focuses on that most dismal of sciences, predicting the future. Forecasting is not just at the heart of Wall Street, but its something each of us does every time we make an insurance payment or strap on a seat belt.
The problem, Nassim explains, is that we place too much weight on the odds that past events will repeat (diligently trying to follow the path of the "millionaire next door," when unrepeatable chance is a better explanation). Instead, the really important events are rare and unpredictable. He calls them Black Swans, which is a reference to a 17th century philosophical thought experiment. In Europe all anyone had ever seen were white swans; indeed, "all swans are white" had long been used as the standard example of a scientific truth. So what was the chance of seeing a black one? Impossible to calculate, or at least they were until 1697, when explorers found Cygnus atratus in Australia.
Nassim argues that most of the really big events in our world are rare and unpredictable, and thus trying to extract generalizable stories to explain them may be emotionally satisfying, but it's practically useless. September 11th is one such example, and stock market crashes are another. Or, as he puts it, "History does not crawl, it jumps." Our assumptions grow out of the bell-curve predictability of what he calls "Mediocristan," while our world is really shaped by the wild powerlaw swings of "Extremistan."
In full disclosure, I'm a long admirer of Taleb's work and a few of my comments on drafts found their way into the book. I, too, look at the world through the powerlaw lens, and I too find that it reveals how many of our assumptions are wrong. But Taleb takes this to a new level with a delightful romp through history, economics, and the frailties of human nature. --Chris Anderson
--This text refers to the Audio CD edition.
In business and government, major money is spent on prediction. Uselessly, according to Taleb, who administers a severe thrashing to MBA- and Nobel Prize-credentialed experts who make their living from economic forecasting. A financial trader and current rebel with a cause, Taleb is mathematically oriented and alludes to statistical concepts that underlie models of prediction, while his expressive energy is expended on roller-coaster passages, bordering on gleeful diatribes, on why experts are wrong. They neglect Taleb's metaphor of "the black swan," whose discovery invalidated the theory that all swans are white. Taleb rides this manifestation of the unpredicted event into a range of phenomena, such as why a book becomes a best-seller or how an entrepreneur becomes a billionaire, taking pit stops with philosophers who have addressed the meaning of the unexpected and confounding. Taleb projects a strong presence here that will tempt outside-the-box thinkers into giving him a look. Gilbert Taylor
Copyright © American Library Association. All rights reserved --This text refers to the Audio CD edition.
Browse award-winning titles. See more
If you are a seller for this product, would you like to suggest updates through seller support?
Top Customer Reviews
In many ways this book tells us things that we all already know, but part of the reason that I believe it is so long is that it needs to systematically go through so many examples of situations that we all use the same type of false logic in, and tell us that it is harmful, no matter how trivial the situation may seem. Embracing what this book is trying to say is painful, and will cause extreme amounts of cognitive dissonance if you are not in the right place. You can generally tell if you fall into that category, when you find yourself picking holes in the edge of the argument for black swans, rather that looking at your held beliefs through the central idea of the book: seeing a million white swans does not confirm the theory that every swan is white, however the sight of one black swan means that the theory is irreparably flawed.
as a real world example, an algorithm that can perfectly predict a normal commodity market and provide consistent returns for 5 years, but is wrong for one day when the market moves 200+% due to a spontaneous crisis, is useless. The one day is the only thing that mattered, while the 20% years of small consistency are the statistical noise.
Most people will always prefer a seemingly solid floor to stand on, even if it prevents them from realizing that they're sinking into the ocean
It is a shame too because for many of us, it spoils the really good main point of the book which is that Black Swans exist, make predictions difficult if not impossible but can be handle in the stock trading business at least by using his barbell approach.
I found the first 1/3 rd of the book very philosophical extremely redundant yet provocative. The rest of the book was much more interesting to me particular the last few chapter which had the most technical discussion and many points to agree with and also to quibble with.
A Black Swan is an extreme event that is very rare but so significant that it creates instability in averages and can ruin predictions and be either castastrophic (the negative Black Swan) or bring great fortune (the positive Black Swan). These Black Swans are real and Taleb cites many examples. Taleb is also right with his point that some economists are blind to the Black Swan or at least the unpredictability of them. I have often seen major declines in the stock market explained after the fact with seemingly logical but very suspicious and dubious rationalizations. Taleb deserves credit for recognizing this and realizing that in the world he calls extremistan where the Black Swans exist they must be accounted for but no should attempt the futile business of predicting them!
He also recognizes that there is another world where the Gaussian distribution and other light-tailed parametric distributions prevail and he calls this the world of mediocrastan. Here, the usual parametric statistics is useful but in Taleb's view it is not very common in practice to be in a mediocrastan world. This is the world of parametric statistics and is the place where most elementary courses in statistics reside. But here is also where I think Taleb makes a big mistake. He assume that this is the world where all statisticians and econometricians live and play and so these teachings are irrelevant to the practical world. Well, in many of the areas he discusses the parametric statistical models do not work. But probabilist, statisticians and econometricians have realized this for at least the past 60 years. In the 1930s and 1940s the field of nonparametric statistics developed through the work of Pitman, Mann and Whitney and Wilcoxon to name a few. Also the theory of extreme value distributions goes back to Fisher and Tippett in 1929 and was rigorously developed by Gnedenko in the 1940s. Nonparametric statistics deals with general distributions that do not have a simple parametric form and includes the heavy-tailed distributions that Taleb cares about. Also the asymptotic theory of extreme values that Fisher and Tippett, Gumbel and Gnedenko discovered showed that the extreme events had systematic behavior based on the three extreme-value types of distributions. So the extremes can be treated using asymptotic statistical theory just as well as the averages can be characterized asymptotically through the central limit theorem and the stable laws (in the case of a heavy-tailed population distribution). So in some ways Taleb is off and out of gas because he doesn't address or perhaps is even ignorant of this theory.
In the area of finance as well as in other areas, time series models have been useful in developing forecasts. In the world of mediocrastan the Box-Jenkins ARIMA models are very useful for problems in forecast and stochastic control. This was well established with the very popular book by Box and Jenkins that was first published in 1970. However financial data often falls into the world of extremistan and the stationary distributions when they exist are non-Gaussian and heavy-tailed. It is in this context that ARIMA models fail but the statisticians and econometricians have developed other models including the GARCH models which handle this type of data and allow for better predictions. Taleb mentions the GARCH models but only to make fun of them in a very superficial way that does not discuss any of the mathematics associated with these models. Again, I am not sure if Taleb is ignorant about this body of literature or just dismisses it because he see other models that cannot be used to predict as more appropriate.
Taleb is enamored with Mandelbrot and his theory of fractal geometry and the apparent natural properties of fractals. Well at least fractals look like coastlines on the world globe as well as other common items in our natural environment. But is this enough to say that fractals are the only models relevant to extremistan? I am not yet convinced.
This August I went to the Joint Statistical Meetings in Denver. There was a session on the Black Swan and to his credit Taleb was brave enough to accept the invitation of the statistical community to come to discuss the issues in his book. Unfortunately, I was not able to attend that session. But it got mew curious enough to want to read the book and see what Taleb's premise was all about. I do not yet know much about what came out of that session. I hope that at least Mr. Taleb came out of it with a better appreciation of the intelligence of statisticians and the more sophisticated models that he appears to be ignorant of based on the lack of discussion of them in his book.
Another branch of nonparametric statistics developed in the 1970s that is now called resampling methods. One of the more successful of these methods is the bootstrap. I have done some research into bootstrap methods as well as having authored a text on the topic. I believe that the bootstrap approach to time series analysis is another way that these time series with non-Gaussian innovation distributions or the stationary distributions of the time series model can be handled. I am not yet convinced that in the world of extremistan the hope of some form of forecasting must be abandoned as is Taleb's thesis.
This work should be read and understood by anyone who makes investments, relies on planning, and believes he has mastered the field of taking risks. This work should be required reading for financial advisers, bankers, insurance executives, and all others who take risks with other people's money.