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Home , Nassim Nicholas Taleb

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 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 , but also, all too often, to serendipitous opportunities. Editor Jan Bots talks with Taleb about chance, 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 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 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, 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 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 , 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 , 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 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. Or CS-First Boston, Banque Indosuez, BNP-Paribas, and take reinsurance. This is just like banking. Insu- the Chicago Mercantile Exchange (a.o.). rance is like mild randomness, reinsurance is wild After (!) in 1987 Taleb was gradually randomness. Very few events can bankrupt insu- able to reduce his financial mathematics activities and rance companies: they reinsure the risks with a low start a second career as an epistemologist of chance probability and a huge repercussion. That is why a events, focusing on the development of his black swan few negative events can bankrupt reinsurance com- theory of unexpected rare events. In 1995 he founded panies. Look at Lloyds: asbestos costs them all their Empirica LLC, which owns interests in hedge funds, savings. If you do a simulation, and you add a large and operates a research laboratory in London. The deviation to reinsurance, you know it will hit them bulk of it’s business consists in portfolio protection hard. Their returns tend to look better than their strategies for hedge funds. real possibilities. Starting September 2007 he will be Professor of If you look at the returns for biotech on the other Marketing (sic) at the hand, they may well be an underestimation of what (visiting 3 months a year) & co-director of the Decision is really there. Particularly in biotech, the returns Science Laboratory. Currently he is on leave as the you see will not include the returns for a potential Dean’s Professor in the Sciences of Uncertainty, cure for baldness; the same way the results of a University of Massachusetts at Amherst, Fellow & reinsurance company will not reflect the major Adjunct Professor of Mathematics at the Courant earthquake in the San Francisco area. Institute of Mathematical Sciences of New York So this is really how I operate. By separating do- University and affiliated faculty, Wharton School mains, whether sensitive or not sensitive, and look- Financial Institutions Center. ing if you are short in options or long in options.

His most succesful publications are Fooled by So how do you construct the ideal portfolio? Randomness: The Hidden Role of Chance in the My ideal portfolio is robust to the negative Black Markets and Life, (1st Ed. November 2001), translated Swan, and sensitive to the positive. If I take tradi- into 19 languages (‘One of the Smartest Books of all tional portfolio theory, and want to construct a me- Time’, Fortune); and The Black Swan: The Impact of dium risk portfolio, it would recommend allocation the Highly Improbable (2007) – a book that may in a broad range of medium risk securities, with a change the way you think about the world. small number of high risk and a small number of low risk opportunities.

MCA: oktober 2007, nummer 6 13 My problem is, I don’t understand their measures dern environments are much more linear to the of risk. Because this is not robust. I can build the number of investments than to the quantities in- same medium risk portfolio by having ninety per- vested. In other words, it is a lot better to do a lot of cent in rather safe treasury bills and ten percent in small speculative investments than a few large di- a massively diversified broad portfolio with high rected ones. Why? risk but also the chance of an extremely positive re- For a fundamental reason, and this is what I call sult. That portfolio is of the same medium risk, but the envelope of serendipity. it is also insensitive to a negative Swan. This I call In The Black Swan I look at the history of technolo- robust. gy, in two fields, engineering and medicine. It be- It is not difficult at all, and I shall demonstrate comes clear firstly that most technology is unpre- this during the Conference in November; there are dictable, whether in the invention or the ways to check the robustness of portfolio’s. I cannot implementation. Only after the fact do we think tell you which one is the most profitable, but I can that there is a pattern, a design. Effectively, our tell which one is the more robust, the less risky. predictive powers are horrendous. We just do not know what will be the next Could you translate this line of thinking breakthrough. Our forecasts for five years are going to management? to be largely ineffectual. But again it is much better I wrote about what I call tinkering in the to invest in a lot of small things, for the very simple Black Swan and elsewhere. It is exactly the same reason that the small things and the big things concept. I discovered that effectively returns in mo- tend to have the same payoff.

14 MCA: oktober 2007, nummer 6 Geoff Delderfield: beeld In my book I took the most influential technologies recast. And still they did not realize that when you of the last 50 years. The top three are the laser (the have to double your forecast in 6 months there is so- basis of the digital revolution), the computer, and mething seriously wrong with your forecast as such. the internet. Now, the internet was not designed I came up with a very simple rule of thumb: a 25 for e-mail or as a place for teenagers to hang around year forecast has in the best of circumstances a bil- in chat rooms. The computer was designed as a cal- lion times bigger error rate than a one-year fore- culating aid, not as a word processor, which turned cast. it into a useful machine, or as a communication The same problem affects climate predictions. tool. The laser was designed by somebody who wan- We may be very good at predicting the weather on to show off by splitting light beams! For years Tuesday. Even in Holland. But predicting climate we did not even know what to do with it. We never change. …Come on! could imagine that it would lead to eye surgery, you This is how I talk about risk. Domain separa- see. tion, based on sensitivity to fat tails. And I have been doing this for twenty years, even as a trader I did. What is your message to business managers? Firstly, if you are shooting for returns, try to get as How can a manager become more sensitive to high an exposure to serendipity as possible. Once negative and positive swans? you find something that looks like it might work, Increasing your sensitivity to upward swans is what invest in it for the max. Like with the 100 books: if I call increasing your envelope of serendipity. In one starts selling, go for it and do everything you short: try everything and keep the good ones. Be can to get more sales. The same happened with willing to take risks, but make sure you cannot lose my book: at first nobody took much notice, but more than x percent. when it hit the NYT bestseller list the whole com- Regarding negative swans: Buy insurance. It pany, , began to get involved. At a usually costs nothing. Never buy insurance on the higher aggregate: look at Bertelsmann. They own highly probable, because it costs a lot. But insuran- so many publishing houses, they publish thou- ce against the improbable, however consequential, sands of books. They really took my idea to the is improbably cheap. max. In our field we now are all busy mitigating risk by How about budgeting where one tries to complying with SOx, in-control statements etc. grasp the future? What do you think about that? I was talking about statistics, not budgets. Budgets Governments have always been very bad at forcing are a necessity. Of course a flexible budget is better risk control. Regulators force you to follow metrics, than a fixed one. I have not looked at budgeting as Icallthisthe ludic fallacy, the belief in very simple such, at the risk of budgeting. But I have looked at models of reality. Regulation may reduce your expo- projections of future cash flows. People who do cash sure to a single event, but usually increases your ex- flow analyses do cash flow projections, without in- posure to other ones. They make you worry about cluding an error rate of past cash flow predictions. If previous problems, but do not lessen the risk for a you were to do this, and indeed included past error new one. Also they force you into metrics, into pro- rates, you can not imagine how shocked you will be. ducing numerical assessments of risks. Nothing is The best example is the billiard ball. What hap- more dangerous than that. pens to the trajectory of a billiard ball? The first bounce is predictable. At the ninth bounce you have Finally, are you pessimistic or optimistic? to accumulate the computational powers of every My idea is not pessimistic, it is optimistic. Look at single person in the room. At the 53d bounce you Google. Most random variables that affect us are must include every single particle in the universe. more positive than negative. My problem is not that The error rate multiplicate. Forecasts of oil prices are we are not good at watching the negative – we are another example. The US government produced a fo- not exposed enough to the positive. recast in January 2004, of 27 dollar per barrel for the next 25 years. Six months later they doubled the fo-

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