View source for Black swan theory

{{Short description|Theory of response to surprise events}}
{{Use dmy dates|date=December 2019}}
[[File:Black swan jan09.jpg|thumb|A black swan (''Cygnus atratus'') in Australia]]

The '''black swan theory''' or '''theory of black swan events''' is a [[metaphor]] that describes an event that comes as a surprise, has a major effect, and is often inappropriately rationalized after the fact with the benefit of [[hindsight]]. The term is based on a Latin expression which presumed that [[black swan]]s did not exist. The expression was used until around 1697 when Dutch mariners saw them in Australia. After this, the term was reinterpreted to mean an unforeseen and consequential event.<ref name=Haworth/>

The theory was developed by [[Nassim Nicholas Taleb]], starting in 2001, to explain:
# The disproportionate role of high-profile, hard-to-predict, and rare events that are beyond the realm of normal expectations in history, science, finance, and technology.
# The non-computability of the probability of consequential rare events using scientific methods (owing to the very nature of small probabilities).
# The [[psychological biases]] that blind people, both individually and collectively, to uncertainty and to the substantial role of rare events in historical affairs.

Taleb's "black swan theory" (which differs from the earlier philosophical versions of the problem) refers only to statistically unexpected events of large magnitude and consequence and their dominant role in history. Such events, considered extreme [[outlier]]s, collectively play vastly larger roles than regular occurrences.<ref name="blackswan_2010">{{cite book |last=Taleb |first=Nassim Nicholas |url=https://books.google.com/books?id=YdOYmYA2TJYC |title=The Black Swan: The Impact of the Highly Improbable |publisher=Penguin |year=2010 |isbn=978-0-14103459-1 |edition=2nd |place=London |access-date=25 April 2020 |orig-year=2007}}</ref>{{rp|xxi}} More technically, in the scientific [[monograph]] "Silent Risk",<ref name="fat_tails_2015" /> Taleb mathematically defines the black swan problem as "stemming from the use of degenerate [[metaprobability]]".<ref name="fat_tails_2015">{{citation |url=http://www.fooledbyrandomness.com/FatTails.html |title=Doing Statistics Under Fat Tails: The Program |date=2015 |access-date=20 January 2016 |first=Nassim Nicholas|last=Taleb}}</ref>

==Background==

The phrase "black swan" derives from a Latin expression; its oldest known occurrence is from the 2nd-century Roman poet [[Juvenal]]'s characterization in his ''[[Satire VI]]'' of something being "''rara avis in terris nigroque simillima cygno''" ("a bird as rare upon the earth as a black swan").<ref name="etruscan_swan">{{cite journal |title=The Origin of Etruscan tusna ("Swan") |first=Jaan |last=Puhvel |journal=The American Journal of Philology |volume=105 |number=2 |date=Summer 1984 |pages=209–212 |publisher=Johns Hopkins University Press |doi= 10.2307/294875 |jstor=294875}}</ref>{{rp|165}}<ref>{{cite book |last1=Juvenal |last2=Persius |last3=Ramsay |first3=George Gilbert |title=Satires |url=https://en.wikisource.org/wiki/Juvenal_and_Persius/The_Satires_of_Juvenal/Satire_6#161 |access-date=23 April 2020 |ref=JuvenalRamsay |publisher=WikiSource|language=en |chapter=[[Satire VI|Satire 6]] |quote='Do you say no worthy wife is to be found among all these crowds?' Well, let her be handsome, charming, rich and fertile; let her have ancient ancestors ranged about her halls; let her be more chaste than the dishevelled Sabine maidens who stopped the war—a prodigy as rare upon the earth as a black swan!}}</ref><ref>{{cite book |last1=Iuvenalis |last2=Bucheler |title=Saturae |publisher=WikiSource |url=https://la.wikisource.org/wiki/Saturae_(Iuvenalis,_Bucheler)/Liber_II |access-date=23 April 2020 |ref=Iuvenalis Bucheler |language=la |chapter=Liber II [[Satire VI|Satura VI]] |quote='nullane de tantis gregibus tibi digna uidetur?' sit formonsa, decens, diues, fecunda, uetustos porticibus disponat auos, intactior omni crinibus effusis bellum dirimente Sabina, rara auis in terris nigroque simillima cycno}}</ref> When the phrase was coined, the [[black swan]] was presumed by Romans not to exist.<ref name=Haworth>{{cite web |last1=Haworth |first1=David |title=Friday essay: a rare bird — how Europeans got the black swan so wrong |url=https://theconversation.com/friday-essay-a-rare-bird-how-europeans-got-the-black-swan-so-wrong-161654 |website=theconversation.com |access-date=March 28, 2024 |date=June 10, 2021}}</ref> The importance of the metaphor 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 logic of any system of thought, 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.<ref>{{cite web |title=Black swan |url=https://forexglossary.com/Black-swan |website=forexglossary.com |access-date=22 September 2021 |archive-date=9 November 2022 |archive-url=https://web.archive.org/web/20221109140727/https://forexglossary.com/Black-swan |url-status=dead }}</ref> The London expression derives from the [[Old World]] presumption that all [[swan]]s must be white because all historical records of swans reported that they had white feathers.<ref>{{cite web|url= http://www.fooledbyrandomness.com/notebook.htm |title=Opacity |website=fooledbyrandomness.com |first=Nassim Nicholas|last=Taleb |access-date= 20 January 2016}}</ref> In that context, a ''black swan'' was impossible or at least nonexistent.

However, in 1697, Dutch explorers led by [[Willem de Vlamingh]] became the [[Black Swan emblems and popular culture#European myth and metaphor|first Europeans to see black swans]], in [[Western Australia]].<ref name=Haworth/> The term subsequently metamorphosed to connote the idea that a perceived impossibility might later be disproved. Taleb notes that in the 19th century, [[John Stuart Mill]] used the ''black swan'' logical fallacy as a new term to identify [[Falsifiability#Deductive falsification|falsification]].<ref name="Hammond_2009">{{citation | first = Peter | last = Hammond | publisher = Warwick | place = UK | url = http://www2.warwick.ac.uk/fac/soc/economics/research/centres/eri/bulletin/2009-10-1/hammond/ | title = Adapting to the entirely unpredictable: black swans, fat tails, aberrant events, and hubristic models | work = WERI Bulletin |date=October 2009 | number = 1 |access-date=20 January 2016}}</ref>

Black swan events were discussed by Taleb in his 2001 book ''[[Fooled By Randomness]]'', which concerned financial events. His 2007 book ''[[The Black Swan (Taleb book)|The Black Swan]]'' extended the metaphor to events outside [[financial markets]]. Taleb regards almost all major scientific discoveries, historical events, and artistic accomplishments as "black swans"—undirected and unpredicted.  He gives the rise of the Internet, the personal computer, [[World War I]], the [[dissolution of the Soviet Union]], and the [[September 11, 2001 attacks]] as examples of black swan events.<ref name="blackswan_2010" />{{rp|prologue}}

Taleb asserts:<ref name="NYT_2007_ch_1">{{cite news| url=https://www.nytimes.com/2007/04/22/books/chapters/0422-1st-tale.html | work= The New York Times | title= The Black Swan: Chapter 1: The Impact of the Highly Improbable | date = 22 April 2007 |access-date=20 January 2016 |last=Taleb|first=Nassim Nicholas}}</ref><blockquote>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.</blockquote>

==Identifying==
Based on the author's criteria:
# The event is a surprise (to the observer).
# The event has a major effect.
# 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.
According to Taleb, the [[COVID-19 pandemic]] was not a black swan, as it was expected with great certainty that a global pandemic would eventually take place.<ref name=":0">{{Cite magazine |date=21 April 2020 |title=The Pandemic Isn't a Black Swan but a Portent of a More Fragile Global System |url=https://www.newyorker.com/news/daily-comment/the-pandemic-isnt-a-black-swan-but-a-portent-of-a-more-fragile-global-system |magazine=[[The New Yorker]]}}</ref><ref name=":1">{{cite web |last=Taleb |first=Nassim Nicholas |date=25 March 2020 |title=Corporate Socialism: The Government is Bailing Out Investors & Managers Not You |url=https://medium.com/incerto/corporate-socialism-the-government-is-bailing-out-investors-managers-not-you-3b31a67bff4a |website=medium.com}}</ref> Instead, it is considered a '''white swan'''—such an event has a major effect, but is compatible with statistical properties.<ref name=":0" /><ref name=":1" />

==Coping with black swans==
The practical aim of Taleb's book is not to attempt to predict events which are unpredictable, but to build ''robustness'' against negative events while still exploiting positive events. Taleb contends that banks and trading firms are very vulnerable to hazardous black swan events and are exposed to unpredictable losses. On the subject of business, and [[Mathematical finance|quantitative finance]] in particular, Taleb critiques the widespread use of the [[normal distribution]] model employed in [[financial engineering]], calling it a ''Great Intellectual Fraud''.  Taleb elaborates the robustness concept as a central topic of his later book, ''[[Antifragile (book)|Antifragile: Things That Gain From Disorder]]''.

In the second edition of ''The Black Swan'', Taleb provides "Ten Principles for a Black-Swan-Robust Society".<ref name="blackswan_2010" />{{rp|374–78}}<ref name="10_prince_">{{citation | url = http://www.fooledbyrandomness.com/tenprinciples.pdf | title = Ten Principles for a Black Swan Robust World | publisher = Fooled by randomness |date=7 April 2009 |access-date=20 January 2016 | first =Nassim Nicholas | last = Taleb}}</ref>

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 to "turn the Black Swans white".<ref>{{cite web |last=Webb |first=Allen |title=Taking improbable events seriously: An interview with the author of The Black Swan (Corporate Finance) |url=http://www.wrap20.com/files/The_Black_Swan.pdf |work=McKinsey Quarterly |publisher=McKinsey |access-date=23 May 2012 |page=3 |format=Interview; PDF |date=December 2008 |quote=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. |url-status=dead |archive-url=https://web.archive.org/web/20120907061933/http://www.wrap20.com/files/The_Black_Swan.pdf |archive-date=7 September 2012  }}</ref>

==Epistemological approach==
Taleb  claims that his black swan is different from the earlier philosophical versions of the problem, specifically in [[epistemology]] (as associated with [[David Hume]], [[John Stuart Mill]], [[Karl Popper]], and others), as it concerns a phenomenon with specific statistical properties which he calls, "the fourth quadrant".<ref name="edge_Taleb_2008">Taleb (2008)</ref>

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 because these are not visible in past samples and therefore require a strong [[a priori and a posteriori|a priori]] (extrapolating) theory; accordingly, predictions of events depend more and more on theories when their probability is small. In the "fourth quadrant", knowledge is uncertain and consequences are large, requiring more robustness.{{Citation needed|date=February 2011}}

According to Taleb, thinkers who came before him who dealt with the notion of the improbable (such as Hume, Mill, and Popper) focused on the [[problem of induction]] in logic, specifically, that of drawing general conclusions from specific observations.<ref>{{cite book|last=Taleb|first=Nassim Nicholas|title=The Black Swan: The Impact of the Highly Improbable|date=April 2007|publisher=Penguin | place = London|isbn=978-1-84614045-7|page = 400|url = https://books.google.com/books?id=_StMPgAACAAJ&q=editions:V_L9FwM6WAgC|edition= 1st|access-date=23 May 2012 }}</ref> The central and unique attribute of Taleb's black swan event is that it 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 bias|hindsight]].{{cn|date=October 2022}} 

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 sometimes assume normal distributions when using [[value at risk]] models, although market returns typically have [[fat tail]] distributions.<ref>Trevir Nath, [http://www.nasdaq.com/article/fat-tail-risk-what-it-means-and-why-you-should-be-aware-of-it-cm537614 "Fat Tail Risk: What It Means and Why You Should Be Aware Of It"], ''NASDAQ'', 2015</ref>

Taleb said:<ref name="NYT_2007_ch_1" /><blockquote>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 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.</blockquote>More generally, [[decision theory]], which is based on a fixed universe or a model of possible outcomes, ignores and minimizes the effect of events that are "outside the 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 September 11, 2001 attacks.  Consequently, the [[New York Stock Exchange]] and [[Nasdaq]] exchange remained closed till September 17, 2001, the most protracted shutdown since the Great Depression.<ref>Palka A Chopra, [https://blogs.mastertrust.co.in/online-trading-during-black-swan-event-covid-19/ "All You Need to Know About Trading During a Black Swan Event"], ''mastertrust'', 2020</ref> A fixed model considers the "known unknowns", but ignores the "[[unknown unknowns]]", made famous by a statement of [[Donald Rumsfeld]].<ref>{{Cite web|url=https://www.defense.gov/News/Transcripts/Transcript/Article/|archiveurl=https://web.archive.org/web/20140903065011/http://www.defense.gov/transcripts/transcript.aspx?transcriptid=2636|url-status=dead|title=Transcript|archivedate=3 September 2014|website=www.defense.gov}}</ref> The term "unknown unknowns" appeared in a 1982 ''[[The New Yorker|New Yorker]]'' article on the aerospace industry, which cites the example of [[metal fatigue]], the cause of [[De Havilland Comet#Early hull losses|crashes in Comet airliners]] in the 1950s.<ref name="Newhouse_1982">{{citation |last=Newhouse |first= J. |title=A reporter at large: a sporty game: i-betting the company |magazine=The New Yorker |date=14 June 1982 |pages= 48–105|url=http://www.newyorker.com/magazine/1982/06/14/a-sporty-game-i-betting-the-company}}</ref> 

Deterministic [[Chaotic dynamical system|chaotic dynamics]] reproducing the Black Swan Event have been researched in economics.<ref>{{cite journal |last1=Orlando |first1=Giuseppe |last2=Zimatore |first2=Giovanna |title=Business cycle modeling between financial crises and black swans: Ornstein–Uhlenbeck stochastic process vs Kaldor deterministic chaotic model |journal=Chaos: An Interdisciplinary Journal of Nonlinear Science |date=14 August 2020 |volume=30 |issue=8 |pages=083129 |doi=10.1063/5.0015916 |pmid=32872798 |bibcode=2020Chaos..30h3129O |s2cid=235909725 |url=https://aip.scitation.org/doi/pdf/10.1063/5.0015916 |language=en |issn=1054-1500}}</ref> That is in agreement with Taleb's comment regarding some distributions which are not usable with precision, but which are more descriptive, such as the [[fractal]], [[power law]], or scalable distributions and that awareness of these might help to temper expectations.<ref>{{cite web| first = Andrew | last = Gelman | title=Nassim Taleb's "The Black Swan"|url = http://andrewgelman.com/2007/04/nassim_talebs_t/ |work=Statistical Modeling, Causal Inference, and Social Science | access-date= 23 May 2012 | author-link = Andrew Gelman | publisher = Columbia University |date=April 2007}}</ref> Beyond this, Taleb emphasizes that many events simply are without precedent, undercutting the basis of this type of reasoning altogether.{{Citation needed|date=February 2022}}

Taleb also argues for the use of [[counterfactual thinking|counterfactual reasoning]] when considering risk.<ref name="NYT_2007_ch_1" />{{rp|p. xvii}}<ref>{{cite web | last =Gangahar|first=Anuj|title=Market Risk: Mispriced risk tests market faith in a prized formula|url = http://www.ft.com/intl/cms/s/0/26c2064e-0b15-11dd-8ccf-0000779fd2ac.html | work = The Financial Times | access-date =23 May 2012|location=New York|date=16 April 2008|archive-url= https://web.archive.org/web/20080420075253/http://www.ft.com/cms/s/0/26c2064e-0b15-11dd-8ccf-0000779fd2ac.html |archive-date=20 April 2008}}</ref>

==See also==
{{colbegin}}
* {{annotated link|Bad beat}}
* {{annotated link|Butterfly effect}}
* {{annotated link|Currency crisis}}
* {{annotated link|Dark horse}}
* {{annotated link|Deus ex machina|''Deus ex machina''}}
* {{annotated link|Domino effect}}
* {{annotated link|Dragon king theory}}
* {{annotated link|Extreme risk}}
* {{annotated link|Falsifiability}}
* {{annotated link|The Gray Rhino: How to Recognize and Act on the Obvious Dangers We Ignore}}
* {{annotated link|Grey swan}}
* {{annotated link|Global catastrophic risk}}
* {{annotated link|Hindsight bias}}
* {{annotated link|Holy grail distribution}}
* {{annotated link|Kurtosis risk}}
* {{annotated link|List of cognitive biases}}
* {{annotated link|Long tail}}
* {{annotated link|Miracle}}
* {{annotated link|Normal Accidents|''Normal Accidents''}}
* {{annotated link|Normalcy bias}}
* {{annotated link|Outside Context Problem}}
* {{annotated link|Perfect storm}}
* {{annotated link|Quasi-empiricism in mathematics}}
* {{annotated link|Rare events}} 
* {{annotated link|Reasonably foreseeable}}
*[[Subjective probability]]
* {{annotated link|Tail risk}}
* {{annotated link|Taleb distribution}}
* {{annotated link|Technological singularity}}
* {{annotated link|There are known knowns}}
* {{annotated link|Uncertainty}}
* {{annotated link|Wild card (foresight)}}
{{colend}}

==References==
{{reflist |32em}}

==Bibliography==
* {{Citation |title=The Black Swan: The Impact of the Highly Improbable |publisher=Penguin |first=Nassim Nicholas |last=Taleb |edition=2nd |year=2010 |orig-year=2007 |place=London |isbn=978-0-14103459-1 |url=https://books.google.com/books?id=gWW4SkJjM08C&pg=PP1 |access-date=26 February 2017}}.
* {{Citation |title= The Fourth Quadrant: A Map of the Limits of Statistics| url = http://www.edge.org/3rd_culture/taleb08/taleb08_index.html | work = Third Culture| publisher = The Edge Foundation | access-date = 23 May 2012| first =Nassim Nicholas | last = Taleb |date=September 2008}}.
* [[:Commons:File:The U.S. response to NEOs- avoiding a black swan event (IA theusresponseton1094550532).pdf|The U.S. response to NEOs- avoiding a black swan event]]

==External links==
* {{Citation | url = https://www.cnbc.com/2012/12/05/black-swan-stocks-could-make-your-portfolio-a-turkey.html | title = Black Swan Stocks Could Make Your Portfolio a Turkey | publisher = CNBC |first=Suzanne |last=McGee |series=Fiscal Times |date=5 December 2012 | access-date=20 January 2016}}.

{{Nassim Nicholas Taleb}}
{{Authority control}}

[[Category:Behavioral economics|Finance]]
[[Category:Epistemological theories]]
[[Category:Metatheory of science]]
[[Category:Black swans|Theory]]
[[Category:Metaphors referring to birds]]
[[Category:Nassim Nicholas Taleb]]