Black swan theory

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For Taleb's book on the subject, see The Black Swan.

The Black Swan theory (in Nassim Nicholas Taleb's version) refers to a large-impact, hard-to-predict, and rare event beyond the realm of normal expectations. Unlike the philosophical "black swan problem", the "Black Swan" theory (capitalized) refers only to events of large consequence and their dominant role in history. Black Swan events may also be called outliers.


[edit] Background

The theory was described by Nassim Nicholas Taleb in his 2007 book The Black Swan. Taleb regards many scientific discoveries as "black swans" — undirected and unpredicted. He gives the rise of the Internet, the personal computer, World War I, and the September 11, 2001 attacks as examples of Black Swan events.[1][2]

The term Black Swan comes from the assumption that 'All swans are white'. In that context, a black swan was a metaphor for something that could not exist. The 17th Century discovery of black swans in Australia metamorphosed the term to connote that the perceived impossibility actually came to pass. Taleb notes that John Stuart Mill first used the Black Swan narrative to discuss falsification.

[edit] Coping with Black Swan Events

The main idea in Taleb's book is not to try to predict Black Swan events, but to build robustness to the negative ones, while being able to exploit positive ones. Taleb contends that banks and trading firms are very vulnerable to hazardous Black Swan events and are exposed to losses beyond that predicted by their defective models.

[edit] Identifying a Black Swan Event

Based on the author's criteria:

  1. The event is a surprise.
  2. The event has a major impact.

After the fact, it is usually the case that the event is rationalized by hindsight, as if it was expected to occur.

[edit] Non-philosophical epistemological approach

Taleb's black swan is different from the earlier (philosophical) versions of the problem as it concerns a phenomenon with specific empirical/statistical properties which he calls "the fourth quadrant".[3] Before Taleb, those who dealt with the notion of the improbable, like Hume, Mill and Popper, focused on the problem of induction in logic, specifically that of drawing general conclusions from specific observations. Taleb's Black Swan has a central and unique attribute: the high impact. His claim is that almost all consequential events in history come from the unexpected—while humans convince themselves that these events are explainable in hindsight (bias).

One problem, labeled the ludic fallacy by Taleb, is the belief that the unstructured randomness found in life resembles the structured randomness found in games. This stems from the assumption that the unexpected can be predicted by extrapolating from variations in statistics based on past observations, especially when these statistics are assumed to represent samples from a bell curve. These concerns are often highly relevant to financial markets, where major players use value at risk models (which imply normal distributions) but market return distributions have fat tails.

More generally, decision theory based on a fixed universe or model of possible outcomes ignores and minimizes the impact of events which are "outside model". For instance, a simple model of daily stock market returns may include extreme moves such as Black Monday (1987) but might not model the market breakdowns following the September 11 attacks. A fixed model considers the "known unknowns", but ignores the "unknown unknowns".

Taleb notes that other distributions are often more descriptive, such as the fractal, power law, or scalable distributions; awareness of these might help to temper expectations.[4] Beyond this, he emphasizes that many events are simply without precedent, undercutting the basis of this sort of reasoning altogether. Taleb also argues for the use of counterfactual reasoning when considering risk.[5][6]

[edit] See also

[edit] Books by Taleb

[edit] References

  1. ^ Nassim Nicholas Taleb, "[1]"
  2. ^ « Nassim Nicholas Taleb - What is a "Black Swan?" »,, 2008-12-21.
  3. ^ The Fourth Quadrant and The Limits of Statistics
  4. ^ Andrew Gelman, Columbia Univ, "Statistical Modeling, Causal Inference, and Social Science"
  5. ^ Nassim Nicholas Taleb, NY Times, "The Black Swan: The Impact of the Highly Improbable" (First Chapter)
  6. ^ ANALYSIS: Mispriced risk tests market faith in a prized formula by Anuj Gangahar (New York), Financial Times. 16 April 2008

[edit] External links

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