Black theory - Wikipedia, the free encyclopedia 23/09/2012 13:03 theory From Wikipedia, the free encyclopedia

The black swan theory or theory of black swan events is a metaphor that describes an event that is a surprise (to the observer), has a major impact, and after the fact is often inappropriately rationalized with the benefit of hindsight.

The theory was developed by to explain:

1. The disproportionate role of high-impact, hard-to-predict, and rare events that are beyond the realm of normal expectations in history, science, finance and technology 2. The non-computability of the probability of the consequential A black swan, a member of the rare events using scientific methods (owing to the very nature species Cygnus atratus of small probabilities) 3. The psychological biases that make people individually and collectively blind to and unaware of the massive role of the rare event in historical affairs

Unlike the earlier philosophical "black swan problem", the "black swan theory" refers only to unexpected events of large magnitude and consequence and their dominant role in history. Such events, considered extreme outliers, collectively play vastly larger roles than regular occurrences.[1]

Contents

1 Background 2 Identifying a black swan event 3 Coping with black swan events 4 Epistemological approach 5 Further developments 5.1 Examples 6 See also 6.1 Books by Taleb 7 References 8 External links

Background

Black swan events were introduced by Nassim Nicholas Taleb in his 2004 book , which concerned financial events. His 2007 book (revised and completed in 2010) The Black Swan extended the metaphor to events outside of financial markets. Taleb regards almost all major scientific discoveries, historical events, and artistic accomplishments as "black "—undirected and unpredicted. He gives the rise of the Internet, the personal computer, World War I, and the September 11 attacks as examples of black swan events.[2]

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The phrase "black swan" derives from a Latin expression; its oldest known occurrence is the poet Juvenal's characterization of something being "rara avis in terris nigroque simillima cygno" ("a rare bird in the lands, very much like a black swan") (6.165).[3] In English, when the phrase was coined, the black swan was presumed not to exist. The importance of the simile lies in its analogy to the fragility of any system of thought. A set of conclusions is potentially undone once any of its fundamental postulates is disproved. In this case, the observation of a single black swan would be the undoing of the phrase's underlying logic, as well as any reasoning that followed from that underlying logic.

Juvenal's phrase was a common expression in 16th century London as a statement of impossibility. The London expression derives from the Old World presumption that all swans must be white because all historical records of swans reported that they had white feathers.[4] In that context, a black swan was impossible or at least nonexistent. After Dutch explorer Willem de Vlamingh discovered black swans in Western Australia in 1697,[5] the term metamorphosed to connote that a perceived impossibility might later be disproven. Taleb notes that in the 19th century used the black swan logical Black swan fallacy as a new term to identify falsification.[citation needed]

Specifically, Taleb asserts[6] in the New York Times:

What we call here a Black Swan (and capitalize it) is an event with the following three attributes. First, it is an outlier, as it lies outside the realm of regular expectations, because nothing in the past can convincingly point to its possibility. Second, it carries an extreme impact. Third, in spite of its outlier status, human nature makes us concoct explanations for its occurrence after the fact, making it explainable and predictable.

I stop and summarize the triplet: rarity, extreme impact, and retrospective (though not prospective) predictability. A small number of Black Swans explains almost everything in our world, from the success of ideas and religions, to the dynamics of historical events, to elements of our own personal lives. Identifying a black swan event

Based on the author's criteria:

1. The event is a surprise (to the observer). 2. The event has a major impact. 3. After the first recorded instance of the event, it is rationalized by hindsight, as if it could have been expected; that is, the relevant data were available but unaccounted for in risk mitigation programs. The same is true for the personal perception by individuals.

An example Taleb uses to explain his theory is the events of 11 September 2001. 9/11 was a shock to all common observers. Its ramifications continue to be felt in many ways: increased levels of security; "preventive" strikes or wars by Western governments. The coordinated, successful attack on the World Trade Center and The Pentagon using commercial airliners was virtually unthinkable at the time. However, with the benefit of hindsight, it has come to be seen as a predictable incident in the context of the changes in terrorist tactics. http://en.wikipedia.org/wiki/Black_swan_theory Page 2 of 7 Black swan theory - Wikipedia, the free encyclopedia 23/09/2012 13:03

Coping with black swan events

The main idea in Taleb's book is not to attempt to predict black swan events, but to build robustness against negative ones that occur and be 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 those predicted by their defective models. On the subject of business in particular, Taleb is highly critical of the widespread use of the normal distribution model as the basis for calculating risk.

In the second edition of The Black Swan, Taleb provides "Ten Principles for a Black-Swan-Robust Society".[7]

Taleb states that a black swan event depends on the observer. For example, what may be a black swan surprise for a turkey is not a black swan surprise to its butcher; hence the objective should be to "avoid being the turkey" by identifying areas of vulnerability in order to "turn the Black Swans white".[8]

Epistemological approach

Taleb's black swan is different from the earlier philosophical versions of the problem, specifically in , as it concerns a phenomenon with specific empirical and statistical properties which he calls, "the fourth quadrant".[9]

Taleb's problem is about epistemic limitations in some parts of the areas covered in decision making. These limitations are twofold: philosophical (mathematical) and empirical (human known epistemic biases). The philosophical problem is about the decrease in knowledge when it comes to rare events as these are not visible in past samples and therefore require a strong a priori, or what one can call an extrapolating theory; accordingly predictions of events depend more and more on theories when their probability is small. In the fourth quadrant, knowledge is both uncertain and consequences are large, requiring more robustness.[citation needed]

According to Taleb,[10] thinkers who came before him who dealt with the notion of the improbable, such as Hume, Mill, and Popper focused on the in logic, specifically, that of drawing general conclusions from specific observations. The central and unique attribute of Taleb's black swan event is high impact. His claim is that almost all consequential events in history come from the unexpected — yet humans later convince themselves that these events are explainable in hindsight.

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 may be predicted by extrapolating from variations in statistics based on past observations, especially when these statistics are presumed to represent samples from a normal distribution. These concerns often are highly relevant in financial markets, where major players use value at risk models, which imply normal distributions, although market returns typically have fat tail distributions.[citation needed]

Taleb: "I don't particularly care about the usual. If you want to get an idea of a friend's temperament, ethics, and personal elegance, you need to look at him under the tests of severe circumstances, not under the regular rosy glow of daily life. Can you assess the danger a criminal poses by examining only what he does on an ordinary day? Can we understand health without considering wild diseases and epidemics? Indeed the normal is often irrelevant. Almost everything in social life is produced by rare but consequential shocks and

http://en.wikipedia.org/wiki/Black_swan_theory Page 3 of 7 Black swan theory - Wikipedia, the free encyclopedia 23/09/2012 13:03 jumps; all the while almost everything studied about social life focuses on the "normal," particularly with "bell curve" methods of inference that tell you close to nothing. Why? Because the bell curve ignores large deviations, cannot handle them, yet makes us confident that we have tamed uncertainty. Its nickname in this book is GIF, Great Intellectual Fraud."

More generally, , based on a fixed universe or a model of possible outcomes, ignores and minimizes the effect of events that 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 breakdown of markets following the 9/11 attacks. A fixed model considers the "known unknowns", but ignores the "unknown unknowns".[citation needed]

Taleb notes that other distributions are not usable with precision, but often are more descriptive, such as the fractal, power law, or scalable distributions and that awareness of these might help to temper expectations.[11]

Beyond this, he emphasizes that many events simply are without precedent, undercutting the basis of this type of reasoning altogether.

Taleb also argues for the use of counterfactual reasoning when considering risk.[12][13] Further developments

Bent Flyvbjerg and Alexander Budzier at Saïd Business School, University of Oxford put forward the concept of Black Swan Blindness in order to explain how decision-makers are commonly surprised by out- of-control events, which often costs them their jobs and even their companies even though they know of Black Swan Events.[14] While black swan blindness has disastrous consequences it itself is caused by well known managerial fallacies, such as:[15]

Illusion of Control Organizational desirability Self-service

The key symptom of black swan blindness are performance management systems that only track averages or expectation values and ignore the variability of performance. The ignorance of an important aspect of risk and uncertainty leads to misguided management attention while exposing organizations to the impact of outlying black swans events.[15]

Examples

Famous examples include:[16]

"Before September 11, 2001, some experts warned that foreign terrorists might try to blow up American office buildings. Those in power did not take these warnings seriously. After all, “it had never happened before.” Many Americans did not know the history of terrorist events in other countries and other decades."[17] The attack on the World Trade Center in 2001 was considered a Black Swan event by those in power at the time.

FoxMeyer Drugs was the 4th largest US pharma distributor with a balance sheet of USD 5bn http://en.wikipedia.org/wiki/Black_swan_theory Page 4 of 7 Black swan theory - Wikipedia, the free encyclopedia 23/09/2012 13:03

headquartered in Carrollton, Texas. FoxMeyer's Black Swan was named Delta III. It kicked-off in 1993 and planned to implement SAP R/3 for financial management as well as Pinnacle for warehouse automation with Andersen as the implementation partner. The system was designed to replace FoxMeyer's mainframe Unisys system to increase the volume it can handle. The project was planned to deliver the new R/3 system and the warehouse automation in 18 month, at costs of USD 65m, and save USD 40m annually. However, not uncommonly SAP and Andersen used the project as a development corporation. The actual cost of the project spiralled to over USD 100m. Thomas Anderson CEO and project champion was forced to leave but the change in leadership came too late. The automation of the warehouse failed and resulted in USD 34m lost inventory. Even more troublesome was the R/3 system performance. FoxMeyer was able to process only 2% of the order volume (10,000 orders per night) that the mainframe system handled. This serious issues in the scalability of the R/3 system came at the time when the company won a major new client. The ICT project erased FoxMeyer's profitability and in 1996 the FoxMeyer was forced into bankruptcy.

The Black Swan for Levi Strauss happened in Q2/2008 when the company's net income dropped by 98% to USD 1m compared to Q2/07. Since 2003 Levi Strauss underwent a major ERP software implementation scheduled to finish in 2010. The global ERP template was first rolled out into the Asian subsidiaries and in 2008 reached the US. The project was designed to replace a complex architecture of Baan in Europe, a bespoke system in Canada and Asia, and the US using a mix of mainframe systems. Levi Strauss tried to clean up the IT architecture to migrate to one common SAP system with the help of implementation partner Deloitte. The project costs were estimated to be between USD 1-5m, excl. consulting fees. Before rolling out the system to the US Levi Strauss was forced to integrate its systems into Wal-Mart's systems increasing the number of complexities in their IT architecture. The company suddenly faced a tremendously different approach to internal controls and only narrowly avoided the need to restate their financial reports. Rolling out new internal financial processes and check procedures lead to a massive hindrance in Levi Strauss' order fulfilment, forcing its three distribution centres in the US to close down for a full week, despite the companies attempt to mitigate the risks by pre-shipping orders in Q1 to wholesalers that normally would have shipped in Q2. The company took a USD 192.5m hit to its bottom-line but was able to absorb this shop. David Bergen the CIO who joined Levi Strauss in 2000 had to leave. Levi Strauss stayed with SAP and is currently undergoing a private cloud experiment to reduce the IT cost.

Hershey's implemented a new order taking and fulfillment system. The project cost USD 112m and comprised a mix of SAP's ERP systems, Siebel's CRM systems, and Manugistic's SCM system supported by Accenture as the integration partner. The project was initially planned to go-live in a Big Bang in June 1999 but the project was delayed by 3 months. During the month of September, however, Hershey's was still fixing errors in its shipping and order fulfillment systems not being able to deliver their products to their customers during the busy Halloween period. In total Hershey's was not able to deliver orders worth USD 100m for Halloween 1999. The news made front page of the Wall Street Journal and stock prices fell 8%. In October, 1999 Hershey's was forced to report a 12.4% drop in quarterly sales to USD 87.6m (earnings -18.6%). The company said computer problems with Hershey's SAP system have created a backlog of orders and slower deliveries. Hershey's stayed with SAP and its CEO Kenneth L Wolfe who eventually retired in 2001. See also

Alain Badiou Butterfly effect Extreme risk

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Kurtosis risk List of cognitive biases Normalcy bias Quasi- in mathematics Randomness Safety of particle collisions at the Large Hadron Collider Taleb distribution The Long Tail Uncertainty Technological singularity

Books by Taleb

Fooled by Randomness The Black Swan Dynamic Hedging – Managing vanilla and Exotic options The Bed of Procrustes: Philosophical and Practical Aphorisms References

1. ^ N.N. Taleb (2010). "Prologue". The Black Swan (Second ed.). Penguin. pp. xxi. 2. ^ N.N. Taleb (2010). "Prologue". The Black Swan (Second ed.). Penguin. 3. ^ JSTOR 294875 (http://www.jstor.org/stable/294875) 4. ^ "Opacity" (http://www.fooledbyrandomness.com/notebook.htm) . Fooledbyrandomness.com. http://www.fooledbyrandomness.com/notebook.htm. Retrieved 2011-10-17. 5. ^ Black Swan Unique to Western Australia (http://web.archive.org/web/20110301051911/http://www.parliament.curriculum.edu.au/wa.php3#symbol) 6. ^ "‘The Black Swan: The Impact of the Highly Improbable'" (http://www.nytimes.com/2007/04/22/books/chapters/0422-1st-tale.html) . The New York Times. 22 April 2007. http://www.nytimes.com/2007/04/22/books/chapters/0422-1st-tale.html. 7. ^ Taleb, Nassim Nicholas (2010). The black swan: the impact of the highly improbable (http://books.google.com/books?id=tXiBZwEACAAJ&dq=isbn:9780141034591&hl=en) (Second ed.). Penguin. p. 374-378. ISBN 9780141034591. http://books.google.com/books? id=tXiBZwEACAAJ&dq=isbn:9780141034591&hl=en. Retrieved 23 May 2012. 8. ^ Webb, Allen (December 2008). "Taking improbable events seriously: An interview with the author of The Black Swan (Corporate Finance)" (http://www.wrap20.com/files/The_Black_Swan.pdf) (Interview). McKinsey Quarterly. McKinsey. p. 3. http://www.wrap20.com/files/The_Black_Swan.pdf. Retrieved 23 May 2012. "Taleb: In fact, I tried in The Black Swan to turn a lot of black swans white! That’s why I kept going on and on against financial theories, financial-risk managers, and people who do quantitative finance." 9. ^ Nassim Nicholas Taleb (September 2008). "The Fourth Quadrant: A Map of the Limits of Statistics" (http://www.edge.org/3rd_culture/taleb08/taleb08_index.html) . Edge Third Culture. The Edge Foundation. http://www.edge.org/3rd_culture/taleb08/taleb08_index.html. Retrieved 23 May 2012. 10. ^ Taleb, Nassim Nicholas (April 2007). The Black Swan: The Impact of the Highly Improbable (http://books.google.com/books?id=_StMPgAACAAJ&dq=editions:V_L9FwM6WAgC) (First ed.). Penguin Ltd. London. pp. 400. ISBN 1846140455. http://books.google.com/books? id=_StMPgAACAAJ&dq=editions:V_L9FwM6WAgC. Retrieved 23 May 2012. 11. ^ Andrew Gelman (April 2007). "Nassim Taleb’s “The Black Swan”" (http://andrewgelman.com/2007/04/nassim_talebs_t/) . Statistical Modeling, Causal Inference, and Social Science. Columbia University. http://andrewgelman.com/2007/04/nassim_talebs_t/. Retrieved 23 May 2012.

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12. ^ Nassim Nicholas Taleb (22 April 2007). "The Black Swan: The Impact of the Highly Improbable, First Chapter" (http://www.nytimes.com/2007/04/22/books/chapters/0422-1st-tale.html) . New York Times. http://www.nytimes.com/2007/04/22/books/chapters/0422-1st-tale.html. 13. ^ Gangahar, Anuj (16 April 2008). "Market Risk: Mispriced risk tests market faith in a prized formula" (http://www.ft.com/intl/cms/s/0/26c2064e-0b15-11dd-8ccf-0000779fd2ac.html) . New York: Financial Times. http://www.ft.com/intl/cms/s/0/26c2064e-0b15-11dd-8ccf-0000779fd2ac.html. Retrieved 23 May 2012. 14. ^ BBC News: Black swans' busting IT budgets (http://www.bbc.co.uk/news/technology-14677143) , 26 August 2011. 15. ^ a b Budzier, Alexander & Flyvbjerg, Bent. Double Whammy - How IT Projects are Fooled by Randomness and Screwed by Political Intent. (http://eureka.sbs.ox.ac.uk/898/) Saïd Business School working paper, August 2011. 16. ^ Flyvbjerg, Bent; Budzier, Alexander (2011). "Why Your IT Project Might Be Riskier Than You Think (http://hbr.org/2011/09/why-your-it-project-may-be-riskier-than-you-think/ar/1) ". Harvard Business Review 89 (9): 23–25. 17. ^ Frankel, Jeffrey (August 20, 2012). "A Flock of Black Swans" (http://www.project-syndicate.org/commentary/a- flock-of-black-swans-by-jeffrey-frankel) . Project Syndicate. http://www.project-syndicate.org/commentary/a-flock- of-black-swans-by-jeffrey-frankel. Retrieved August 20, 2012. External links

The Fourth Quadrant and The Limits of Statistics (http://www.edge.org/3rd_culture/taleb08/taleb08_index.html) -Taleb's concept of the limits of statistics Ten Principles for a Black Swan Robust World (http://www.fooledbyrandomness.com/tenprinciples.pdf) Dr. Gil David, Black Swans in the Cyber Domain (http://www.israeldefense.com/? CategoryID=512&ArticleID=1297)

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