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8NewsletterJune 2008CFA Conference FeaturesThe Impact of the Highly Improbable:Randomness and Black Swan BlindnessVicky Ng, CFAOver the past 12 months a number ofevents have rocked the financial markets,and how many of us can honestly say thatwe clearly anticipated such incidents or theirseverity? Speaking at the CFA Institute AnnualConference in Vancouver on May 12, NassimNicholas Taleb explained why extreme eventsare hard to predict and why these eventsoften have catastrophic impacts. Currently avisiting professor at London Business Schooland formerly dean’s professor in the sciencesof uncertainty at the University of Massachusetts,Professor Taleb is the author of Fooledby Randomness and more recently The BlackSwan: The Impact of the Highly Improbable,two highly regarded books that discuss, oftenthrough anecdote, Taleb’s thoughts on howuncertainty works.such theory is valid only in situations of “mildrandomness”, a world he calls Mediocristan.For example, adding one additional datapoint to a reasonably large sample set of humanheights will probably not greatly changethe distributive properties of the set becauseextreme human heights are not that far fromthe mean. In contrast, adding the annualincome of the world’s richest person to arandom sample set of the incomes of 10,000people would change the sample distributionconsiderably. In other words, in some casesa small number of occurrences can accountfor a large proportion of the total outcome.Another example is that there are about267,000 drugs available on the market, butonly 5% of all drugs account for most of theprofits of pharmaceutical companies. TalebNassim Nicholas TalebIn his presentation, Taleb explained that thecentral problem concerning extreme eventsis that the smaller an event’s probability, thelarger our sample set must be to reliablyestimate that probability, and as the probabilitybecomes smaller the more consequentialthe impact of any error in estimating it willbe on the magnitude of the actual outcome.Investors and others in the prediction businesshave to be conscious not only of theuncertain probability of extreme events, butalso the uncertain magnitude, good or bad,of these events. How, he asked, do analystsjustify labelling something a 1-in-10,000-yearevent when their sample sets cannot covernearly so long a time period? His answer:purely from theory.Mediocristan vs. ExtremistanModern portfolio management often usesstatistical theory based on the Gaussiandistribution (the normal distribution) toforecast event probabilities. Taleb believes“I shiver at the thought that something fails.”provided further examples, pointing out thatTo illustrate the difficulty in more worldlytail distributions dominate the likelihood ofterms, Taleb compared the characteristicssocial and economic events. These situationsof government change in Italy and in Saudibelong to another world, one that TalebArabia: the Italian government changes frequentlyand somewhat unpredictably (highcalls Extremistan. He warns that there is noreliable structure in the probability distributionsof Extremistan.volatility), but each change has relatively littleimpact; the Saudi government changes verylittle (low volatility), but a change in governmentcould have a severe impact in manyTaleb believes that statistics and probabilityestimates are irrelevant in forecastingways (consider the 1979 revolution in Iran).extreme events and our world is shaped byPrognosticators also suffer from the fallacy ofthe dynamics of Extremistan. Although mostsingle event probability. Events in Extremistanpeople rely on past experience (i.e. data fromdo not follow a typical pattern. One mightprevious periods) to forecast the future, pastsuccessfully predict the occurrence of anextreme probability distributions – generallyreferred to as tail distributions – areevent yet be totally wrong about the formthat the event actually takes. An examplenot indicative of future extreme probabilityof this was the confidence of many knowldistributions:previous outliers do not predictfuture outliers.Continued on next page.
NewsletterJune 20089“Unobserved Incentives and the Impact of Economics on Daily Life” continued from page 4.In one case, a consumer electronics companyapproached him for marketing advice. For along time, this company had used both TVadvertising three times a year and full-pageads in Sunday newspapers every week ineach major newspaper market. Consultantsbrought into investigate the effectiveness ofthis advertising had reported a high correlationbetween sales and the TV advertising,but found that the newspaper advertisingwas much less effective. Levitt was suspiciousof these findings and found that the TVadvertising had coincided with dates suchas Christmas and Fathers’ Day when sales arehigher than normal regardless of advertising.In other words, the consultants had confusedcorrelation with causality.Levitt suggested testing the newspaperadvertising effectiveness through an experimentwhere the company would stop advertisingin selected markets and compare salesin those markets with sales in markets wherethe ads continued. The company refused todo this, since the local salespeople in the firstset of markets would be up in arms if newspaperadvertising was interrupted. Interestingly,Levitt found that such an ‘experiment’had been done inadvertently: an intern’smistake had led to no newspaper ads in thePittsburgh market for three months – withoutany noticeable impact on sales. Despite thisevidence, which Levitt felt warranted a morethorough test, the company continues toadvertise in the Sunday papers every weekwithout knowing if this is a total waste ofmoney. Such is the battle against conventionalwisdom!During the Q & A session, Levitt was askedwhat incentives the government shouldprovide to prevent the sort of problems thathave damaged the CDO and credit marketssince last summer.After commenting on various aspects of thisissue, stating that “if you give people badincentives, then things go wrong”, he opinedthat a government bailout is the worst thingto do since “you can’t reward people for makingbad economic choices”, drawing applausefrom the audience.“The Impact of the Highly Improbable: Randomness and Black Swan Blindness” continued from page 8.edgeable people in 1914 that a few weeks oflimited battle would be enough to decide theoutcome of what tragically became the FirstWorld War.Taleb stated that we therefore need toconsider two layers of stochasticity – one regardingevent occurrence and one regardingan event’s impact. Even if we could reliablypredict the probability distribution of an extremeevent, it will remain difficult to predictthe event’s consequences.Moving on to discuss financial institutions, Talebsaid that the global banking system usedto look like the governance situation in Italy,but now looks more like that in Saudi Arabia– “I shiver at the thought that something fails”.As the banking network (and other networkssuch as power transmission grids) comes toconsist of fewer but larger entities, there willprobably be fewer and fewer small shocks(e.g., bank runs), but network effects due toconcentration and nonlinearities could makelarge, infrequent shocks more consequentialthan in the past.Hedge fund returns are a case of life inExtremistan. A problem in the hedge industrycited by Taleb is that a steady stream ofpositive returns (suggestive of an option-writingstrategy) can be suddenly followed by asuddenly ruinous negative return. One causeof this problem is the difference betweenthe time scale used for manager compensationand that needed to realistically analyzeperformance data – a hedge fund managerwill be well compensated during the steadyperformance periods, but when disasterstrikes investors could lose all their profitseven though the manager keeps any bonusesbased on previous gains. Taleb believes thatmany investors expose themselves to such ahazard because they do not understand thenature of risk. For example, some people failto recognize that exposure to a 1-in-30-yearevent is still risky even if their exposure lastsfor only 15 years.During Q & A, Taleb prescribed the use ofqualitative methods in Extremistan to avoidthe pitfalls of black swans and wonders whyanybody would rely on a single number tomeasure risk, especially one already provento be a poor measure. He also reminded theaudience that black swans can have a positiveimpact, but cautioned that good black swansusually happen over time while bad blackswans tend to go “Boom!”.
Page 1 and 2: NewsletterJune 2008Inside:Editor’
Page 3 and 4: President’s LetterAnna Nemeth, CI
Page 5 and 6: Investment ThemeThis is Your Brain
Page 7: Investment Theme“This is Your Bra
Page 11 and 12: NewsletterJune 200811Member ReportW

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