Just posted on Nassim’s Facebook Wall:
Nassim Nicholas Taleb
Looks like a preview of what to expect from the economics and econophaster establishment. Davies is the gentleman there; others have not even given a simple thougth to model error and which domains are affected by it. But asking people to explain insults can lead to pleasant surprises.
When Taleb met Davies:
This morning, Nassim Taleb returned to Twitter, posting one of the technical appendices to his new book. And immediately he got into a wonderfully wonky twitterfight/conversation with Daniel Davies.
I don’t pretend to understand all the subtleties of the conversation between the two, but, for Tom Foster, here’s an attempt. Davies has promised a Crooked Timber post on other parts of the appendix; I’m really looking forward to that.
Read the rest here…
Nassim Taleb has linked to a new paper on his Facebook Page: How We Tend To Overestimate Powerlaw Tail Exponents
In the presence of a layer of metaprobabilities (from metadistribution of the parameters), the asymptotic tail exponent corresponds to the lowest possible tail exponent regardless of its probability. The problem explains “Black Swan” effects, i.e., why measurements tend to chronically underestimate tail contributions, rather than merely deliver imprecise but unbiased estimates.
Nassim Taleb has shared a new paper in PDF form on his Facebook Page titled: How We Tend To Overestimate Powerlaw Tail Exponents
In the presence of a layer of metaprobabilities (from metadistribution of the parameters), the asymptotic tail exponent corresponds to the lowest possible tail exponent regardless of its probability. The problem explains “Black Swan” problems, i.e., why measurements tend to chronically underestimate tail effects, rather than merely deliver imprecise but unbiased estimates.
The Bloomberg Businessweek website has a feature piece on Robert Rubin, in the article Nassim is interviewed and shares his view on President Clinton’s former Treasury Secretary and former Citigroup executive.
“Nobody on this planet represents more vividly the scam of the banking industry,” says Nassim Nicholas Taleb, author of The Black Swan. “He made $120 million from Citibank, which was technically insolvent. And now we, the taxpayers, are paying for it.”
Nassim Nicholas Taleb doesn’t know Rubin personally. He admits that his antipathy, like that of so many Rubin critics, is fueled by symbolism. “He represents everything that’s bad in America,” he says. “The evil in one person represented. When we write the history, he will be seen as the John Gotti of our era. He’s the Teflon Don of Wall Street.” Taleb wants systemic change to prevent what he terms the “Bob Rubin Problem”—the commingling of Wall Street interests and the public trust—“so people like him don’t exist.”
Nassim Taleb has released a paper with the IMF: A New Heuristic Measure of Fragility and Tail Risks: Application to Stress Testing
From Business Insider: NASSIM TALEB: The Fed Is Looking At The Banking System All Wrong
Nassim Taleb has long been a critic of traditional forecasting methods like the ones underlying these stress tests. He even coined a now oft-repeated term to capture his criticism – “black swan” – which became a huge New York Times bestselling book.
Now, he warns that “fragility is especially high for the banks with the worst outcomes” according to a new metric he’s developed to better analyze the risks facing the banks.
In a new white paper with researchers at the IMF, Taleb explains the reason why all of the stress tests conducted by central banks and international financial institutions like the Federal Reserve, the ECB, and the IMF come up short:
First, many stress tests focus on the point estimates of very few scenarios, and often pay little attention to how the impact would change in case of different scenarios, e.g., a slightly more severe one. Second, if stress tests do not take into account the possibility of model and parameter error, it can be misleading to rely only on the point estimates of even well-designed stress tests. Without considering the potential for these errors, one could miss the convexities/non-linearities that can lead to serious financial fragilities.
A better approach, according to Taleb and his IMF co-authors Elie Canetti, Tidiane Kinda, Elena Loukoianova, and Christian Schmeider, is to measure the difference between outcomes arising from different scenarios instead of focusing on the estimates of potential losses themselves.
According to Taleb, this is the real way to measure the “fragility” of a bank or a country in the event of a negative economic shock. Because point estimates are so prone to errors from faulty model assumptions, measuring the distance between them to detect how quickly losses pile up as the economic shock gets larger becomes a vastly more reliable measure of risk.
In other words, it’s not the size of the losses themselves that is important. Instead, it’s the rate of change of potential losses as the economic situation deteriorates that determines how fragile a bank is, by Taleb’s standards.
Nassim Taleb has released a technical note for Antifragile on his Facebook Page: Why the One Percent of the One Percent benefit from inequality more than general prosperity: A Note for AntiFragile.
The one percent of the one percent of the population is vastly more sensitive to inequality than total GDP growth (which explains why the superrich are doing well now, and should do better under globalization, and why it is a segment that doesn’t correlate well with the economy). For the super-rich, one point of GINI causes an increase equivalent to 6-10% increase in total income (say, GDP). More generally, the partial expectation in the tail is vastly more sensitive to changes in scale of the distribution than in its centering.
Sellers of luxury goods and products for the superwealthy profit from dispersion more than increase in total wealth or income. I looked at their case as a long optionality, benefit-from-volatility type of industry.
Another business that does not care about the average but rather the dispersion around the average is the luxury goods industry—jewelry, watches, art, expensive apartments in fancy locations, expensive collec – tor wines, gourmet farm – raised probiotic dog food, etc. Such businesses only cares about the pool of funds available to the very rich. If the population in the Western world had an average income of fifty thousand dollars, with no inequality at all, the luxury goods sellers would not survive. But if the average stays the same, with a high degree of inequality, with some incomes higher than two million dollars, and potentially some incomes higher than ten million, then the business has plenty of customers—even if such high incomes were offset with masses of people with lower incomes. The “tails” of the distribution on the higher end of the income brackets, the extreme, are much more determined by changes in inequality than changes in the average. It gains from dispersion, hence is antifragile.
This explains the bubble in real estate prices in Central London, determined by inequality in Russia and the Arabian Gulf and totally independent of the real estate dynamics in Britain. Some apartments, those for the very rich, sell for twenty times the average per square foot of a building a few blocks away.
Harvard’ s former president Larry Summers got in trouble explaining a version of the point and lost his job in the aftermath of the uproar. He was trying to say that males and females have equal intelligence, but the male population has more variations and dispersion (hence volatility), with more highly unintelligent men, and more highly intelligent ones. For Summers, this explained why men were overrepresented in the sci – entific and intellectual community (and also why men were overrepre – sented in jails or failures). The number of successful scientists depends on the “tails,” the extremes, rather than the average. Just as an option does not care about the adverse outcomes, or an author does not care about the haters.
A reader has sent in a copy of Nassim’s Lecture notes from when he was teaching a course at the University of Massachusetts, Amherst, MA in 2005. The course/lecture series are titled: Randomness, Decisions, and Human Nature (SOM 797R – SYLLABUS).
Unfortunately all the links within the PDF are missing, if anyone has a copy with all the working links to studies, research papers, books, articles, images, etc, please let us know!
>> Check it out here.