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Nassim Taleb: You Cannot Become Fat in One Day, but You Can Become Enormously Wealthy!

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Nassim Taleb: You Cannot Become Fat in One Day, but You Can Become Enormously Wealthy! Interview: NASSIM TALEB: YOU CANNOT BECOME FAT IN ONE DAY, BUT YOU CAN BECOME ENORMOUSLY WEALTHY! On November 7 the Controllers Institute will hold it’s annual conference. One of the more interesting, but maybe less well-known keynote speakers will be Nassim Nicholas Taleb, author of bestsellers Fooled By Randomness and more recently The Black Swan. Taleb divides our environment in Mediocristan and Extremistan; two domains in which the ability to understand the past and predict the future is radically different. In Mediocristan, events are generated by an underlying random process with a ‘normal’ distribution. These events are often physical and observable and they tend to cluster in a Gaussian distribution pattern, around the middle. Most people are near the average height and no adult is more than nine feet tall. But in Extremistan, the right-hand tail of events is thick and long and the outlier, the wildly unlikely event (with either enormously positive or enormously negative consequences) is more common than our general experience would indicate. Bill Gates is more than a little wealthier than the average. 9/11 was worse than just a typical bad day in New York City. Taleb states that too often in dealing with events of Extremistan we use our Mediocristan intuitions. We turn a blind eye to the unexpected. To risks, but also, all too often, to serendipitous opportunities. Editor Jan Bots talks with Taleb about chance, risk and how to cope with it in the real world. Professor Taleb, how would you introduce yourself specialized in complex derivatives on the one hand, to our readers? and probability theory on the other. I looked at the I consider myself a scholar, who specializes in un- errors in judgment when dealing with probability. certainty. I used to be a stock trader for a very long I have a PhD in applied statistics, but from ’87 time, but since the crash of 1987 I luckily did not this interest evolved into an interest in the role of have to worry much about the more mundane. So I large events. But: seen from all kinds of perspecti- 10 MCA: oktober 2007, nummer 6 ‘A Black Swan is an event with a very small probability, but huge repercussions’ MCA: oktober 2007, nummer 6 11 ‘There are ways to check the robustness of portfolio’s’ ves – philosophy, psychology, economics, history, social sciences, all blended together. one day. This is the world of predictability. Becom- I was never interested in finance per se. I was ing rich or poor is the domain of wild randomness. interested in what I could learn from finance. You can easily become rich (97% of the money I ever When people ask you ‘What are you?’ they usually made came in one day, in October 1987) or poor mean ‘What job are you being paid for?’ Now no- (war, earthquake) in a single day. body pays me a salary… I do what I do. How do you know or determine in which Not every reader will be familiar with your two domain you are? books, Fooled by Randomness and The Black Swan. Pretty much everything socio-economic is in the Could you summarize their message for us? domain of wild randomness, especially when it is Really, the Black Swan summarizes it all I think. linked with information. There are ways to do diag- Rare events, what I call Black Swans, play a massive nostics from the role of random variables. For in- role. A Black Swan is an event with a very small pro- stance with books: you just calculate the share of bability, but huge repercussions. Before it happens the minority in the total. Or you can perform an ex- we never even think about it. Then, after the fact, ante analysis by asking the question whether there we realize it really had been predictable, but that are natural limits to the variable, as in the height or our science was not very effective: we apparently weight of people. In socio-economics you seldom have a huge amount of retrospective predictability have natural limits. skills, but no effective prospective ones. These rare events play an monumental role in But if I take the example of book publishing, our lives – whether in finance, in economics, poli- my publisher knows his rule-of-thumb: tics, war and peace, or inventions. The world as it that only 2 out of 100 titles will be a success. appears is not very predictable, because it depends Yes, but he does not know beforehand which ones. on concentrated random variables. We may think Nor will he know whether he’ll sell a thousand or a we can model it; we cannot, because the outliers do- million copies. In some years 70% comes from seven minate. In history books you’ll read that the first books, in other years 50% from twenty. You can pu- world war was predictable. But if you look at war blish books for ten years and never have a hit. bonds, it was not. They predicted 1870, but not 1914. Fact is, our ability to generalize from sample This war was only retrospectively predictable. People sets is monstrously low. If you look at biotech, can- were lulled by a century of post-Napoleonic peace. cer research for example, we have been doing that One metaphor I use to explain this is book sales. for 40 years now without any real breakthrough. In 1995 there were maybe 10.000 books published in The last one, chemotherapy, by the way was an se- the States. 70% of the sales revenue was generated rendipitous invention. by five titles: outliers, statistically seen. Likewise, How long did we have to wait for Microsoft? Bill Gates is infinitely more wealthy than most Another example: Google. other people. We are living in a world in which first of all If you consider the role of large deviations in there is great uncertainty about these random vari- wealth, market share, casualties in war, it is so ables. potent; it makes everything unpredictable. What I noticed in my research, and that is more or less my business now, is the following: I probably And how do we cope with this unpredictability? cannot figure out all these probabilities, but what We can do a lot about this, if we start to perform we are very good at is determining whether my what I call domain separation. There are two kinds world is sensitive to these random variables, to an of domains. One, in which a large deviation plays outlier or not. That is very easy to ascertain. an inconsequential role, what I call mild random- ness. In the other domain, of wild randomness, de- That then is the big question? viations play a massive role. Eating is an example of Yes. Take portfolio’s. There are portfolio’s, sensitive mild randomness: the quantity of food you can ab- to what I call the negative Black Swans, and portfo- sorb in one day is limited. You can not become fat in lio’s that are sensitive to positive Black Swans. 12 MCA: oktober 2007, nummer 6 NASSIM TALEB Nassim Nicholas Taleb (b. 1960) is an essayist, belletrist & scholar, only interested in one single topic – chance, or rather rare events with a very small probability but huge repercussions. Born in Lebanon, in the 1980s, after attending university in France, he entered the Wharton MBA program at the University of Pennsylvania. In an options theory class, he felt an immediate affinity for Did you know, in 1982 banks in America lost cumu- the product. ‘It was effortless for me to think about latively 800% of all the profits made in the history options,’ he reflects. ‘So I told myself, “Hey, it's a of banking. Of course with the consent of Paul Vol- great way to be lazy. Lazy and intuitive.”’ In 1985 he cker this was kept hidden. The eight biggest banks began trading at Bankers Trust and quickly discovered in America had $ 22 bn in capital, and $ 60 bn in that rare events were more frequent than people loans to South and Central America. They lost believed – and that when they happened, they cost a everything in one incident. You see, you can tell lot more than people expected they would. That was right away if you are in an environment that is sen- when he first began formulating his own way of looking sitive to negative Black Swans. at rare events. This made him turn towards Ten years later, with the Savings &Loans fiasco, mathematics. ‘I started studying the mathematics of they made the same mistake again! This one cost us distributions to understand options better,’ he says, 700 bn dollars. And now they may do it again. In ‘so I'd have to work even less for a living.’ other words, banking is an industry, very sensitive He now describes his options trading as a ‘hobby’ (‘I to Black Swans. was not interested in finance per se, but rather in what Now let’s take an industry that is sensitive to I could learn from it.’). As a pioneer of complex positive Black Swans, real estate. Real estate has financial derivatives Taleb is a legend; his book been, in America and elsewhere, very profitable, Dynamic Hedging: Managing Vanilla and Exotic particularly when you borrow from banks, who are Options (1996) is the Bible of the options trade. He short in options. So real estate entrepreneurs have worked for institutions like Union Bank of Switzerland, always had the upside, and banks the downside.
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