Monthly Archives: June 2009

SSRN-Too Big to Fail, Hidden Risks, and the Fallacy of Large Institutions by Nassim Taleb

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PDF available for download at link location.

Too Big to Fail, Hidden Risks, and the Fallacy of Large Institutions

Nassim Nicholas Taleb
NYU-Poly Institute; London Business School

May 2, 2009

Large institutions are disproportionately more fragile to Black Swans.
This paper establishes the case for a fallacy of economies of scale in large aggregate institutions. The problem of rogue trading is taken as a case example of hidden risks where rogue traders and losses are considered independently and dependently of the institution’s size. Both independent and dependent loss and hidden positions are shown to lead to the paper’s conclusion, that size and economies of scale have commensurate risks that mitigate the advantages of size.

SSRN-Errors, Robustness, and the Fourth Quadrant by Nassim Taleb

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Another paper written by NNT. PDF available for download at link location.

Errors, Robustness, and the Fourth Quadrant

Nassim Nicholas Taleb
NYU-Poly Institute; London Business School

February 14, 2009

The paper presents evidence that econometric techniques based on variance- L2 norm are flawed -and do not replicate. The result is un-computability of role of tail events. The paper proposes a methodology to calibrate decisions to the degree (and computability) of forecast error. It classifies decision payoffs in two types: simple payoffs (true/false or binary) and complex (higher moments); and randomness into type-1 (thin tails) and type-2 (true fat tails) and shows the errors for the estimation of small probability payoffs for type 2 randomness. The Fourth Quadrant is where payoffs are complex with type-2 randomness. We propose solutions to mitigate the effect of the Fourth Quadrant based on the nature of complex systems.

SSRN-Finiteness of Variance is Irrelevant in the Practice of Quantitative Finance by Nassim Taleb

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Paper written by NNT.

Finiteness of Variance is Irrelevant in the Practice of Quantitative Finance

Nassim Nicholas Taleb
NYU-Poly Institute; London Business School

June 09, 2008

Outside the Platonic world of financial models, assuming the underlying distribution is a scalable power law, we are unable to find a consequential difference between finite and infinite variance models – a central distinction emphasized in the econophysics literature and the financial economics tradition. While distributions with power law tail exponents α>2 are held to be amenable to Gaussian tools, owing to their finite variance, we fail to understand the difference in the application with other power laws (1<α<2) held to belong to the Pareto-Lévy-Mandelbrot stable regime. The problem invalidates derivatives theory (dynamic hedging arguments) and portfolio construction based on mean-variance. This paper discusses methods to deal with the implications of the point in a real world setting.

Technical Appendix -TBS

The result of that blog entry, and of a few other criticisms of Taleb in various places, is that Nassim has now published an extremely useful technical appendix to The Black Swan. It includes substantially all his relevant scientific and technical papers, and essentially comprises a gauntlet being thrown down to those who would criticize him. If you want to attack my ideas, he’s saying, that’s fine, but please first do me the favor of looking at where they’re laid out in detail, as opposed to where they’re laid out in newspaper quotes or in a literary book.

The Black Swan Technical Appendix

Some people make technical comments on a literary book (TBS was presented as aliterary-philosophical essay), but do not go after my technical works thatpresent analytical discussions and empirical evidence. I find it flattering (ifunchallenging) to only be attacked in the wrong places, but it is more honestand more helpful for scientific progress (and more dignified) if the technical authorscommented on technical works AND DID NOT DISSEMINATE A WRONG PRESENTATION ABOUTMY IDEAS (Fama, Scholes,Engle, etc.) Actually, no: this is VERYdishonest. I will consider it bad faith toattack the statistical statements in my literary work without looking at thetechnical documents and will not spare any shady academic who does so.

The Fourth Quadrant

Where I explain the problems, show how to deal with it(“what to do about the Black Swan”) and provide exhaustive DATA:

Technical version: Errors,Robustness, and the Fourth Quadrant, International Journal of Forecasting, 2010,(in Press)

Literary/philosophical version on

Exposition of my problem tostatisticians: Black Swan and Domains of Statistics, The American Statistician, August 2007,Vol. 61, No. 3

The Gaussian-NonGaussian Problem

Somebad-faith commentators (say like Richard Bookstaberor Eugene Fama) are distorting my idea: TBS is not “against the Gaussian”,but largely the apriorism in the measurement of tailevents and the consequences of errors (see the epistemology papers). The papers below show how the problemis not “Gaussian-NonGaussian” but related theconvergence to the Central Limit Theorem in real time. Domain 1 converges toCLT (fat tails or not), Domain 2 does not (finite variance or not). Fama is still trapped in the 1960s paradigm Gaussian v/sPareto-Levy-Mandelbrot basin; I believe that 1) we do not converge the PLM inreal time (preasymptotics), and 2) we suffer fromsevere inverse problems as we do not observe distributions.

I summarize: the three problems are:

· Pre-asymptotics (all that happens takes place outside the limit),

· InverseProblems(many models can explain the same phenomena), and

· Platonicities (the reduction of the fool)

all thesame illness under different symptoms.

Finiteness of Variance is Irrelevant in the Practiceof Quantitative Finance, my paper in Complexity, 14(2)

Note with Benoit Mandelbrot on Pre-Asymptotics and extreme values of probability distributions, in Mandelbrot, B. and Taleb, N.N. (in Press).Random Jump, not Random Walk. In Francis Diebold and Richard Herring (Eds.), The Known, the Unknown, and the Unknowable,Princeton University Press

Platonic convergence & theCentral Limit Theorem. (technical notes)

Epistemological Problems (The Apriori role in theestimation of small probabilities)

My central problem

The A PrioriProblem of Observed Probabilities, (technical note)

Why probability does not matter, but impact:

The fundamental problem of the0th moment and the irrelevance of”naked probability”

Literary discussion on Real Lifeis Not a Casino , forthcoming in Brockman et al, 2009

Inverse problems of probabilities:

I problemi epistemologici del riskmanagement in: Daniele Pace (a cura di)Economia del rischio. Antologia di scritti surischio e decisione economica, Giuffrè, Milano

Risk andEpistemology (with Avital Pilpel) Risk andRegulation (LSE)

On the VeryUnfortunate Problem of Not Observing Probability Distributions (workingpaper, with Avital Pilpel)

Essay in theEpistemology of Power Laws (Wilmott,2005),

Techne-Episteme Problem (Rationalism v/sEmpiricism)

Haug, E.G.and Taleb, N.N. (2008) Why We Have Never Used the Black-Scholes-MertonOption Pricing Formula, Wilmott magazine

10 – Principles : What Needs to Break Should Break Early

Taleb andTapiero, 2009 (forthcoming) – We show why too big is too fragile for the Black Swan.

Psychological Experiments and Discussions

“The Telescope Problem”, Taleb and Goldstein (forthcoming, submitted to Science) – The natural intuitionsare domain dependent.

“Risk and Framing”, Taleb and Goldstein (forthcoming, submitted to Science) – The natural intuitionsare domain dependent.

“Non-neutrality of risk measures” –whya risk measure makes you take MORE risk, regardless of its accuracy.

Goldstein, D.G. and Taleb, N.N. (2007) We Don’t Quite Know What We Are Talking About When WeTalk About Volatility, Journalof Portfolio Management, Summer 2007.

Taleb, N.N. (2004) “Bleed or Blowup: What Does Empirical Psychology Tell Us About thePreference For Negative Skewness? ”, Journal ofBehavioral Finance, 5

Derivatives Pricing

OptionPricing & True Fat tails

Why Do People Like to Truncate the Upside? Call sellersfool themselves with the illusion of statistical properties (technicalnote)