Too Big To Fail

Nassim Taleb and Charles Tapiero has penned down a new technical article "Too Big to Fail, Too Big to Bear". I am reproducing the article here:

Electronic copy available at: http://ssrn.com/abstract=1497973
Center for Risk Engineering, New York University Polytechnic Institute Page 1
Too Big to Fail, Too Big to Bear,
and Risk Externalities
Nassim N. Taleb*
Charles S. Tapiero*
Abstract
This paper examines the risk externalities stemming from the size of institutions. The problem of
excessive risk taking and their potential external consequences are taken as a case example. Assuming
(conservatively) that a firm risk exposure is limited to its capital while its external (and random) losses
are unbounded we establish a condition for a firm to be too big to fail. In particular, expected risk
externalities’ losses conditions for positive first and second derivatives with respect to the firm capital are
derived. Examples and analytical results are obtained based on firms’ random effects on their external
losses (their risk externalities) and policy implications are drawn that assess both the effects of “too big to
fail firms” and their regulation.
Key words: Risk, Externalities, Economies of Scale
• Department of Finance and Risk Engineering, New York University Polytechnic Institute, The
Research Center for Risk Engineering, New York and Brooklyn.

Electronic copy available at: http://ssrn.com/abstract=1497973
Center for Risk Engineering, New York University Polytechnic Institute Page 2
1. Introduction
“Too Big to Fail” is a dilemma that has plagued economists, policy makers and the public at large. The
lure for “size” embedded in “economies of scale” and Adam Smith factories have important risk
consequences that have not always been assessed or properly defined. Economies of scales underlie the
growth of industrial and financial firms ([6]) to sizes that may be both too large to manage and losses too
large to bear. This is the case for industrial giants such as GM that have grown into a complex and
diversified global enterprise with extremely large failure risk externalities. This is also the case for large
banks that bear risks with systemic consequences that are often ignored and too big to bear. Banks, unlike
industrial firms, draw their legal rights from a common trust, to manage the supply and the management
of money for their own and the common good. Their failure, overflowing into the “Commons”, may thus
far outstrip their internal and direct losses. The losses borne by the “Commons” can be an appreciable
risk externality that banks do not assume. Further, when banks are perceived too big to fail, they may
have a propensity to assume excessive risks to profit in the short term; they may seek to exercise unduly
their market power; rule the “Commons” and price their services unrelated to their costs or quality.
Size may lead such firms to assume leverage risks that are unsustainable. This is the case when banks’
bonuses are indexed to short term performance, at the expense of sustainable performance hard to
quantify risk externalities. Externality is then an expression of market failure. For banks that are too big
to fail, these risk externalities are acute. For example, Frank Rich (The New York Times, Goldman Can
Spare You a Dime, October 18, 2009) has called attention to the fact that “Wall Street, not Main Street,
still rules Washington”. Similarly, Rolfe Winkler (Reuters) pointed out that “Main Street still owns much
of the risk while Wall Street gets all the profits”. Further, a recent study by the National Academy of
Sciences has pointed out to extremely large hidden costs to the energy industry—costs that are not
accounted for by the energy industry, but assumed by the public at large.
Banks and Central Banks rather than Governments, are entrusted to manage responsibly the monetary
policy—not to be used for their own and selfish needs, not to rule the “Commons”, but to the betterment
of society and the supply of the credit needed for a proper functioning of financial markets. A violation
of this trust has contributed to a financial meltdown and to the large consequences borne by the public at
large. In this case, “too big to fail banks” have contributed to an immense negative externality—costs
experienced by the public at large. In this sense, markets with appreciable negative externalities are no
longer efficient, even if we have perfect competition (i.e. complete financial markets). If a firm’s
negative externalities are not compensated by their positive externalities or appropriately regulated, then
their social risks can be substantial. In a recent New York Times article (Sunday Business, section,
October 4, 2009), Gretchen Morgension, referring to a research paper of Dean Baker and Travis
McArthur, indicated the effects of selective failures, letting selected banks grow larger and “subsidized”
at a cost of over 34 Billion dollars yearly over an appreciable amount of time.
Size is no cure to the failure of firms. For example, Fujiara [4], using an exhaustive list of Japanese
bankruptcy data in 1997 (see [2],[3],[5],[8],[10]) has pointed out to firms failure regardless of their size.
Further, since the growth of firms has been fed by debt, the risk borne by large firms seems to have
increased significantly—threatening both the creditor and the borrower. In fact, the growth of size
through a growth of indebtedness combined with “too big to fail” risk attitudes has ushered, has
contributed to a moral hazard risk, with firms assuming non-sustainable growth strategies on the one hand

Center for Risk Engineering, New York University Polytechnic Institute Page 3
and important risk externalities on the other. Furthermore, when size is based on intensely networked
firm (such as large “supply chains”) supply chain risks (see also [15], [16] and [7]) may contribute as well
to the costs of maintaining such industrial and financial organizations. Saito [11] for example, while
examining inter-firm networks noted that larger firms tend to have more inter-firms relationships than
smaller ones and are therefore more dependent, augmenting their risks. In particular, they point out that
Toyota purchases intermediate products and raw materials from a large number of firms; maintaining
close relationships with numerous commercial and investment banks; with a concurrent organization
based on a large number of affiliated firms. Such networks have augmented both dependence and supply
chains risks. Such dependence is particularly acute when one supplier may control a critical part needed
for the proper function of the whole firm. For example, a small plant in Normandie (France) with no
more than a hundred employees could strike out the whole Renault complex. By the same token, a small
number of traders at AIG could bring such a “too big to fail” firm to a bankrupt state. This networking
growth is thus both a result and a condition for the growth to sizeable firms of scale free characteristic
(see also [3],[5]). Simulation experiments to that effect were conducted by Alexsiejuk and Holyst [1]
while constructing a simple model of bank bankruptcies using percolation theory on a network of
cooperating banks (see also [12] on percolation theory). Their simulation have shown that sudden
withdrawals from a bank can have dramatic effects on the bank stability and may force a bank into
bankruptcy in a short time if it does not receive assistance from other banks.
More importantly however, the bankruptcy of a simple bank can start a contagious failure of banks
concluded by a systemic financial failure. As a result, too big to fail and its many associated moral
hazard and risk externalities is a presumption that while driving current financial policy and protecting
some financial and industrial conglomerates (with other entities facing the test of the market on their own
and subsidizing such a policy), can be extremely risky for the public at large.
Size for such large entities thus matters as it provides a safety net and a guarantee by public authorities
that whatever their policy, their survivability is assured at the expense of public funding. The strategic
pursuit of economies of scales can therefore be misleading, based on fallacies that negate the risks of size,
do not account for latent and dependent risks, their moral hazard and significant risk externalities.
The essential question is therefore can economies of scale savings compensate their risks. Such an issue
has been implicitly recognized by Obama’s administration proposals in Congressional committees
calling for banks to hold more capital with which to absorb losses. The bigger the bank, the higher the
capital requirement should be (New York Times, July, 27, 2009, Editorial). However such regulation
does not protect the “commons” from the risk externalities that banks create and the common sustains.
To assess the effects of size and their risk externalities, this paper considers a particular and simple case
based on a firm risk exposure which can lead to a firm’s demise (its capital) and unbounded external
losses for which they assume no consequence. An example is used to demonstrate that such risk exposure
underlying excessive risk taking (motivated by the lure for short term profits) can have accelerating losses
the larger the bank.

Center for Risk Engineering, New York University Polytechnic Institute Page 4
2. Too Big Too Fail and Its Risk Externality.
Given the nature of a speculative position, we assume that the positions has a potential loss probability
distribution bounded above by the firm aggregate capital (its size, consisting of its equity and debt
holdings) or . In some cases, the speculative exposure of trades may be larger
than a firm’s capital. Further, a bank’s loss can have a repercussion on other external losses—the larger
the bank’s loss, the larger the potential external loss. Given a firm’s loss, we let its total loss, including
external losses be given by . As a result, the joint probability distribution of
global financial and firm losses is . A loss resulting
from a firm random exposure of its capital W has thus probability and cumulative distributions:
The effects of size on the aggregate loss are thus a compounded function of the probabilities of losses of
the firm and their external costs. If a firm has a loss whose external consequences (the loss y are
extremely large), then they may be deemed to be “too big to fail” as the negative externalities of its failure
may be too big to bear. In this context, the risks of “too big to fail” firms are similar to “polluters”, the
the greater their risk externalities, the greater their pollution.
The example we consider below assumes a Pareto probability distribution ([9]) for losses conditional on
the bank’s loss. Conditional external losses are bounded below by the bank loss (its capital) and
unbounded above. While, aggregate losses are a mixture probability distribution of the aggregate external
losses. These assumptions result in a fractional hazard rate model bounded by the bank’s capital.
Internal risk exposure (the banks’ capital at risk) is assumed to have an extreme truncated probability to
account for its finite capital at risk. In particular we use a truncated Weibull probability distribution.
Our approach differs from the Copula approach that models co-dependence of losses by the marginal
distribution of each distribution. It also differs from a generalization of the Pareto distribution (or other
probability distributions) that accounts for a potential correlation between the firm and its external losses.
Both such approaches are not be applicable in our case as external losses depend necessarily on the firm
losses but not vice versa. In other words, we assume that external losses are not causal to a bank’s loss
but a bank’s loss is causal to external losses borne by the public at large.
Further, while an inter-temporal framework based on Levy-Wiener processes and fractal diffusion models
can be considered as well, its use is not essential to prove the essential results of this paper. Such an
extension will be considered in a subsequent paper however. The case considered is thus selected for
simplicity and to highlight the effects of a bank’s potential capital loss on its external losses.
Explicitly, let the conditional loss Pareto distribution be:
The loss distribution parameter may be interpreted as the expected loss multiplier “odds” effect for a
given (risk exposure) loss by the bank. The expected external loss is thus . The larger the
“odds” the larger its the risk externalities. For example if a firm loss of 7 Billion dollars has an external
loss of 65 Billion dollars, its parameter is or and .
By the same token since,

Center for Risk Engineering, New York University Polytechnic Institute Page 5
The expected externality multiplier odds effect odds can be further scored and assessed by a logit
distribution. Explicitly, say that:
Then: and with a score defined as a function of both the loss and
economic environmental conditions. A bank whose internal loss is its capital, contribute then to an
expected loss of:
Where is a “Too Big To Bear” index, the larger the index, the larger the external losses and the more
a bank is “too big to fail”. In other words, letting a total capital loss of of 50 Billion dollars, the failure of
the bank’s loss is
Billion dollars.
The unconditional loss probability distribution is then:
The probability of a loss greater than Y and its hazard rate are therefore,
and
If a firm’s expected external loss is then and if it is too big to fail
then . In this case, the external risks of “size” are nonlinear, growing infinitely as the
bank’s size increases.
For demonstration purposes, say that the probability distribution is a constrained extreme
(Weibull) distribution defined by,
The loss probability distribution and its cumulative distribution function are then:
With expected losses:

Center for Risk Engineering, New York University Polytechnic Institute Page 6
The effects of the firm capital size on the expected losses are thus:
The second derivative leads to:
or
Since
The condition for a positive second derivative is:
These conditions establish therefore the conditions for an accelerating loss the larger the firm—a loss that
may be far larger than the firm capital loss.

Center for Risk Engineering, New York University Polytechnic Institute Page 7
Conclusion
The purpose of this paper is to indicate that size matters and its risk externalities may be too big to bear—
in which case firm may be too big to fail. Such firms are “polluters” either by design when they overleverage
their financial bets or speculative positions and are struck by a Black Swan [13], [14]. While
capital set aside (such as VaR—V alue at Risk) may be used to protect their internal losses, such
approaches are oblivious to the far morte important risk extrnalities. For this reason, such firms require
far greater attention and far more regulation. Internalizing risk externalities by ever larger firms is in such
cases inappropriate since the moral hazard and the market power resulting from such sizes will be too
great. Similarly, total controls, total regulation, taxation, nationalization etc. are also a poor answer to
deal with risk externalities. Such actions may stifle financial innovation and technology and create
disincentives to an efficicent allocation of money. Coase observed that a key feature of externalities are
not simply the result of one CEO or Bank, but the result of combined actions of two or more parties. In
the financial sector, there are two predominant parties, Banks that are “too big to fail” and the
Government—a stand in for the public. Banks are entrusted rights granted by the Government and
therefore any violation of the trust (and not only a loss by the bank) would justify either the removal of
this trust or a takeover of the bank. A bargaining over externalities would, economically lead to Pareto
efficient solutions provided that banking and public rights are fully transparent. However, the nontransparent
bonuses that CEOs of large banks apply to themselves while not a factor in banks failure is a
violation of the trust signaled by the incentives that banks have created to maintain the payments they
distribute to themselves. For these reasons, too big too fail banks may entail too large too bear risk
externalities. The result we have obtained indicate that this is a fact when banks internal risks have an
extreme probability distribution (as this is often the case in VaR studies) and when external risks are an
unbounded Pareto distribution.
References:
[1] A Aleksiejuk, J.A.Holyst, A simple model of bank bankruptcies, Physica A, 299, 2001, 198-204
[2] L.A.N. Amaral, S.V. Bulkdyrev, S.V. Havlin, H. Leschron, P. Mass, M.A. Salinger, H.E. Stanley,
M.H.R. Stanley , J. Phys I, France, 1997, 621.
[3] J.P. Bouchaud, M. Potters, Theory of Financial Risks and Derivatives Pricing, From Statistical
Physics to Risk Management, 2nd Ed., , 2003, Cambridge University Press.
[4] Y. Fujiwara, Zipf law in firms bankruptcy, Physica A, 337, 2004, 219-230

Center for Risk Engineering, New York University Polytechnic Institute Page 8
[5] D. Garlaschelli, S. Battiston, M. Castri, VDP Servedio, G.Caldarelli, The scale free nature of market
investment network, Physica A, 350, 2005, 491-499
[6] Y. Ijiri, H.A. Simon, Skew distributions and the size of business firms, North Holland, New York,
1977
[7] Konstantin Kogan and Charles S. Tapiero, Supply Chain Games: Operations Management and Risk
Valuation, Springer Verlag, Series in Operations Research and Management Science, (Frederick Hillier
Editor), 2007
[8] K. Okuyama, M. Takayasu, H. Takayasu, Zipf’ss Law in income distribution of companies, Physica
A, 269, 1999, 125-131
[9] V. Pareto, Le cours d’Economie Politique, Macmillan, London, 1896
[10] M.H.R. Stanley, L.A.N. Amaral, S.V. Bulkdyrev, S.V. Havlin, H. Leschron, P. Mass, M.A. Salinger,
H.E. Stanley, Nature, 397, 1996, 804
[11] Y.U. Saito, T. Watanabe and M. Iwamura, Do larger firms have more interfirm relationships,
Physica A, 383, 2007, 158-163,
[12] D. Stauffer, Introduction to Percolation Theory, Taylor and Francis, London and Philadelphia, A,
1985.
[13] N.N. Taleb, The Black Swan: The Impact of the Highly Improbable, Random House, New York and
Penguin Books, London 2008
[14] NN. Taleb, Errors, Robustness, and The Fourth Quadrant, Forthcoming, International Journal of
Forecasting, 2009
[15] C.S. Tapiero, Consumers risk and quality control in a collaborative supply chain, European Journal
of Operations Research, 182, 683–694, 2007
[16] Tapiero, C. S., Risk Finance and Financial Engineering (tentative title), Wiley, 2010, (Forthcoming,
2 volumes)

Lecturing Birds on Flying

Lecturing Birds

The Poker Face of Wall Street

I came across this great Book " The Poker Face of Wall Street" by Aaron Brown. It is turning out to be a great read. Incidentally, the foreword is written by Nassim Taleb. So, it automaticaly becomes a must read for all of Taleb's Fans. Here is a little piece from Taleb's foreword to the book:


"One would tend to think that gambling is a sterile activity that is
meant to occupy those who have not much else to do and others
when they have not much else to do. You would also think that there
is a distinction between “economic risk taking” and “gambling,” one
of them invested with respectability, the other treated as a vice and a
product of a parasitic activity."

Myron Scholes' pathetic response to Nassim Taleb

Myron Scholes finally responded, in a pathetic manner, to Nassim Taleb's criticism. With Taleb now being the leader in revolt against the Modern House of Finance and Mathematical Models adopted to measure risk, had this to say about Myron Shcoles: "we have to unmask the charlatans of risk like Myron Scholes".Taleb was quite furious on Scholes. He considers Scholes as the Great Oz because his work on options and derivatives allowed the whole of the financial system to adopt poorly understood products-like the ones that brought AIG down-that hide risk. To Taleb, Scholes' academic work, which enabled the widespread use of complex derivatives, was like 'giving children dynamite.' 'This guy should be in a retirement home doing Sudoku,' Taleb says. 'His funds have blown up twice. He shouldn't be allowed in Washington to lecture anyone on risk.'" Michael Lewis too commented on hazards and harms that the use of Black Scholes Model has brought upon the financial health- "Black-Scholes didn’t work; trillions of dollars’ worth of securities may have been priced without regard to the possibility of crashes and panics. But until very recently, no one has bitched and moaned about this problem too loudly. Lay folk might harbor private misgivings about the clergy, but as lay folk, they are reluctant to express them. Now, however, as the subprime market unravels, the beginnings of a revolt against the church seem to be taking shape".

I had expected that the fathers of Financial Horoscope Models would come up with some decent answer or better still would admit the flaws in their Models with open heart. But, it looks like they dont have the gut and unfortunately still continue to live in fool's paradise. Still sticking to their guns they are not even sophisticated to give a decent reply. All Scholes could say to Taleb's criticism was " If someone says to you, “Go to an old-folks’ home,” that’s kind of ridiculous, because a lot of old people are doing terrific things for society. I never tried sudoku. Maybe he spends his time doing sudoku".

The Legend of Nassim Taleb Part 2

Somewhere on http://www.fooledbyrandomness.com Taleb is pessimistic about any change in the way the global house of finance and public policy operates. This he states as his fear despite the fact that The Black Swan has become an all time Bestselling Book in the fields of Economics or Finance. So I have started some research and trying to assess about the reach of Taleb's teachings and ideas. Further to my earlier post here are some more Books that discuss or incorporate Taleb's Ideas:

1- Derivatives: Models on Models By Espen Gaarder Haug. And here is how Haug describes Nassim: " Nassim Taleb was an original thinker a tail event himself, specializing in tail events. He was also not afraid of sharing his knowledge probably because he knew that human nature and the bonus system in most wall street firms would make most traders ignore his ideas anyway.

2- The Long Tail: Why the Future of Business is Selling Less of More
By Chris Anderson
3- Traders, guns & money: knowns and unknowns in the dazzling world of derivatives
By Satyajit Das
4- Identifying and Managing Project Risk By Tom Kendrick: The Author calls 'The Black Swans" the most serious problems.
5- Handbook for Surviving the Global Financial Crisis By Barbara Goldsmith. The Book seems to be a guide to survive the hazards of next black swan yet the author seems to have completely ignored what Taleb had to himself said in this regard.

Contiued...........

Now that I have started it all, it is hard to stop. But it is becoming evident to me that Taleb and his Books have become a great source of reference for varied fields. I desperately need volunteers to continue and broaden the work.

Nassim on Reuters

One stop for almost all that is there on The Black Swan and Taleb

I came across this great site http://www.theblackswanreport.com . The site is full of great stuff related to Nassim Taleb's work and is updated regularly with latest material. It has lots of Videos, Interviews, articles and links. A wonderful one stop free shop for Taleb's Fans

Nassim on Bloomberg, Says Geithner Plan bound to fail

Nassim Taleb Full lengthwith Charlie Rose

Randall On 'Discovery Of Black Swan'

http://video.aol.com/video-detail/randall-on-and039discovery-of-blackswanand039/492626517

What caused the current Financial Crisis

In near future we are going to see book shops filled with Books on what caused the current financial crisis. But you realy dont need that. Nassim Taleb sums it up all along with the ways to deal with the crisis . The Master Genius takes only five minutes to explain it all. Watch and enjoy the video. 

Nassim Taleb Video Presentation at LongNow Foundation

Nassim Nicholas Taleb presentation on The Black Swan. This is over one hour video. Probably, the longest video presentation avaialable on net. I have converted the format to 3gp, to reduce the size. Anyone interested in better quality video, please email me motasim.ahmad@gmail.com  . 

Taleb Takes Alan Greenspan To Task

Nassim Nicholas Taleb has turned his guns to Alan Greenspan- quite rightly so.

Sitting 17 weeks on the New York Times best-seller list, “Black Swan” outsold former U.S. Federal Reserve Governor Alan Greenspan's “The Age of Turbulence” months ago.
So, how does it feel?
“Greenspan is an empty suit,” he told the Turkish Daily News in Istanbul, one of the latest stops on his lecture tour. “He does not understand economic life and he does not know that he doesn't know. And his book is boring. I despise the man.”
Taleb says the turmoil vindicates him once again. “Greenspan is a man who plays with economic life without understanding its basic structure. In today's world, links between action and consequences are not as visible as they were in the past.”
A major mistake of Greenspan was letting the banking system cluster, he said. “Thus, you end up with a gigantic bank and lose the natural ecology. If a restaurant does not give decent food, the owner goes bust. But banks get clustered. So you end up with one single source of risk and that is JP Morgan!”
“In the U.S., you trade with any bank, you are trading with JP Morgan. I barked about this for years, but then Bear Stearns went bust and JP Morgan ended up taking it,” he said. For Taleb, a system that banks do not go bust means a system that risk is highly concentrated.
He cited an example from another realm. “Which one has more political volatility? Italy or Saudi Arabia? Of course Italy, because they had 62 governments since World War II. But Saudi Arabia has had the same family in power since you guys left them,” he said, referring to the Ottoman Empire. “But Italy has much less risk than Saudi Arabia.”
So, some entities like Bear Stearns do not have volatility but are very risky, while some that are risky do not have volatility. “Greenspan and others do not understand this,” he said. “They never let the banks fail. I want them to fail, because I love the banking system. Finance is too important to be left to U.S. central bankers.”
In his trading days, Taleb was a legend due to a few incredible “hits.” The most legendary of these was in 1987, when he was working for First Boston. At 28 years of age, he made the right bet on Eurodollar futures when nobody else did. On Oct. 19, the Dow Jones Industrial Average declined 22.6 percent, the biggest one-day drop in the United States ever. Eurodollar futures surged after the Fed pumped liquidity into the banking system in a rush, lowering interbank borrowing rates.

Investment choices:
The majority of his personal fortune today is still based on that lucky day. His choice of investing that fortune tells something about Taleb's philosophy. “I like things that are volatile. Instead of investing in medium-risk securities, I invested 90 percent in no-risk government bonds. But my 10 percent is in extremely risky choices.”
“Some businesses, such as biotech, or emerging markets, can benefit from the black swan,” he said. “The problem is, some businesses, like banks in the U.S., have a lot of downside exposure, but no upside exposure.”
The basic rule for Taleb is simple: “If you need a mathematician to understand what you have in your books, you're a blowup.”
“I trained lots of these people,” he continued. “And I tell you, my students were incompetent. I would not give them my car to drive, or even to wash. Mathematics does not work in real life.”
Does “Extremistan” mean the old saying that history repeats itself is not valid anymore? “People tend to learn first order from history. The best example would be the Maginot Line. When Germans came, the French built a wall. What did the Germans do? They went around it,” he continued. “First order thinking is like, ‘Let's make sure we are prepared for a second 22 percent stock market crash.' Because it had never been that worse. But then, the 22 percent crash did not have a predecessor, so history would not have taught you that.”
Taleb has told “the guys at Morgan Stanley” that they are “morons” precisely because of that. “They were doing historical stress testing on their subprime portfolio. But how can you do that when history does not have a predecessor?”
Then he explains his “second order thinking” so rapidly, one might think he cannot repeat these words again: “There is a past, the past's past and the past's future. Then there is today, today's past and today's future. You should work with today's future in relation to today's past the way the past's future worked with the past's past.”
“Simple peasants understand this thinking. But bring in someone with a PhD who works at a bank on risk management, he does not. It's like autism. Thus, the more mathematicians you have in a bank, the more likely it is to blow up.”

From Lebanon to war on terror:
A political “black swan” from Taleb's childhood was the Lebanese civil war. “Nobody saw it coming,” he said. “My father was telling me that it would be over in a week. It went on 17 years. But today, the black swan for Lebanon is peace.”
The black swan takes on another quality if it is spotted. “Anytime you identify a source of randomness, you overestimate its probability and commit mistakes,” Taleb explained. “Today we overestimate terrorism. Give a retard like [George W.] Bush an army and he starts inventing sources of risk.”
The biggest source of risk for humankind is not terrorism but diabetes, which kills 80 million people every year, he argued. “Our reaction to terror causes more people to die than terrorism itself. Nearly 3,000 people died on Sept. 11, 2001. But in the aftermath, many more died due to traffic accidents because they were afraid of flying.” Nearly 600 extra deaths on U.S. and European roads per month after 9/11, he said.
If diabetes is the biggest source of risk today, economists come after it. “We have too many economists,” he said. “The Federal Reserve is dangerous. So is Davos. All pseudo-experts.”

Overoptimization:
Now, this reporter was warned before the interview that Taleb was a “hard one to crack,” and a couple of previous interviews went astray due to colleagues' insistence on asking his prediction on oil prices, the U.S. dollar or the Turkish economy.
This time, Taleb answers without receiving the question in some sort of verbal preemptive strike. “Why did the price of food and oil rise so much?” he said himself. “Because the system is too optimized. A small imbalance of 1 percent in the demand for wheat causes prices to double. But if you look at the facts, demand for wheat is up 2 percent while supply is up 5 percent.”
Such vast price swings tell us that “forecastability in that domain is worse.” So, nobody can guarantee that a barrel of oil will not cost $40 the next day, instead of continuing its rise toward $140. And that is why Taleb is reluctant to predict.
Then, is there an alternative to be paranoid and expect the unexpected? Maybe one has to look at what Karl Marx had said decades ago, a suggestion surprisingly made by prominent businessman İshak Alaton in April.
Taleb strongly disagrees. “According to Marx, the idea is how to turn knowledge into action, and that is pure enlightenment arrogance,” he said. “My point is how to turn absence of knowledge and understanding into action.”
For that, the world has to wait for “Tinkering,” the next book of the trader-turned-philosopher. Until then, ranks of Taleb fans are sure to get more crowded. The world is hungry for new ideas and perspectives, a common phenomenon for times of such deep crises. And that is exactly what Taleb delivers.

Mandelbrot on Modern Portfolio Theory

Individual investors and professional
stock and currency
traders know better than ever
that prices quoted in any financial market often
change with heart-stopping swiftness. Fortunes are
made and lost in sudden bursts of activity when the market
seems to speed up and the volatility soars. Last September,
for instance, the stock for Alcatel, a French telecommunications
equipment manufacturer, dropped about 40 percent
one day and fell another 6 percent over the next few days. In a
reversal, the stock shot up 10 percent on the fourth day.
The classical financial models used for most of this century
predict that such precipitous events should never happen. A
cornerstone of finance is modern portfolio theory, which tries
to maximize returns for a given level of risk. The mathematics
underlying portfolio theory handles extreme situations with
benign neglect: it regards large market shifts as too unlikely to
matter or as impossible to take into account. It is true that
portfolio theory may account for what occurs 95 percent of
the time in the market. But the picture it presents does not
reflect reality, if one agrees that major events are part of the
remaining 5 percent. An inescapable analogy is that of a sailor
at sea. If the weather is moderate 95 percent of the time, can
the mariner afford to ignore the possibility of a typhoon?
The risk-reducing formulas behind portfolio theory rely on
a number of demanding and ultimately unfounded premises.
First, they suggest that price changes are statistically independent
of one another: for example, that today’s price has no
influence on the changes between the current price and tomorrow’s.
As a result, predictions of future market movements
become impossible. The second presumption is that all
price changes are distributed in a pattern that conforms to
the standard bell curve. The width of the bell shape (as measured
by its sigma, or standard deviation)
depicts how far price changes
diverge from the mean; events at the extremes
are considered extremely rare. Typhoons
are, in effect, defined out of existence.
Do financial data neatly conform to such assumptions?
Of course, they never do. Charts of stock or currency changes
over time do reveal a constant background of small up and
down price movements—but not as uniform as one would
expect if price changes fit the bell curve. These patterns, however,
constitute only one aspect of the graph. A substantial
number of sudden large changes—spikes on the chart that
shoot up and down as with the Alcatel stock—stand out
from the background of more moderate perturbations.
Moreover, the magnitude of price movements (both large
and small) may remain roughly constant for a year, and then
suddenly the variability may increase for an extended period.
Big price jumps become more common as the turbulence of
the market grows—clusters of them appear on the chart.
According to portfolio theory, the probability of these large
fluctuations would be a few millionths of a millionth of a millionth
of a millionth. (The fluctuations are greater than 10
standard deviations.) But in fact, one observes spikes on a regular
basis—as often as every month—and their probability
amounts to a few hundredths. Granted, the bell curve is often
described as normal—or, more precisely, as the normal distribution.
But should financial markets then be described as abnormal?
Of course not—they are what they are, and it is portfolio
theory that is flawed.
Modern portfolio theory poses a danger to those who believe
in it too strongly and is a powerful challenge for the theoretician.
Though sometimes acknowledging faults in the
present body of thinking, its adherents suggest that no other
premises can be handled through mathematical
modeling. This contention leads to the
question of whether a rigorous quantitative description
of at least some features of major financial upheavals can be
developed. The bearish answer is that large market swings
are anomalies, individual “acts of God” that present no conceivable
regularity. Revisionists correct the questionable
premises of modern portfolio theory through small fixes that
lack any guiding principle and do not improve matters
sufficiently. My own work—carried out over many years—
takes a very different and decidedly bullish position.
I claim that variations in financial prices can be accounted
for by a model derived from my work in fractal geometry.
Fractals—or their later elaboration, called multifractals—do
not purport to predict the future with certainty. But they do
create a more realistic picture of market risks. Given the recent
troubles confronting the large investment pools called
hedge funds, it would be foolhardy not to investigate models
providing more accurate estimates of risk.

Sub Prime mess- A nail in the coffin of Traditional Risk Management

About three years ago when I was fascinated by Economists and used to read on daily basis a lot of economic commentary, almost every one focused on China as next epicenter of economic chaos. No one, not a single soul suspected the great USA. Now the mess seems to be getting out of control. The Black Swan by Nassim Nicholas Taleb offers explanation for such blindness. It was only after the sub prime crisis that people started agreeing with his ideas to a greater extent. The traditional risk management techniques failed comprehensively. Now, I think , the whole discipline of risk management needs to be rebuild and much of it would be based on Taleb's philosophy.

Here is the first indication:

Death of VaR Evoked as Risk-Taking Vim Meets Taleb
Jan. 28 (Bloomberg) -- The risk-taking model that emboldened Wall Street to trade with impunity is broken and everyone from Merrill Lynch & Co. Chief Executive Officer John Thain to Morgan Stanley Chief Financial Officer Colm Kelleher is coming to the realization that no algorithm or triple-A rating can substitute for old-fashioned due diligence.Value at risk, the measure banks use to calculate the maximum their trades can lose each day, failed to detect the scope of the U.S. subprime mortgage market's collapse as it triggered more than $130 billion of losses since June for the biggest securities firms led by Citigroup Inc., Merrill, Morgan Stanley and UBS AG.The past six months have exposed the flaws of a financial measure based on historical prices that securities firms use idiosyncratically and that doesn't anticipate every potential disaster, such as the mistaken credit ratings on defaulted subprime debt.``Finance is an area that's dominated by rare events,'' said Nassim Taleb, a research professor at London Business School and former options trader. ``The tools we have in quantitative finance do not work in what I call the `Black Swan' domain.''Taleb's book ``The Black Swan,'' published last year by Random House, describes how people underestimate the impact of infrequent occurrences. Just as it was assumed that all swans were white until the first black species was spotted in Australia during the 17th century, historical analysis is an inadequate way to judge risk, he said. for full articlehttp://www.bloomberg.com/apps/news?pid=20601109&sid=axo1oswvqx4s&refer=home