The Black Swan deals with the “impact of the highly improbable” and argues that these events, dubbed Black Swans, are far more common then we think, in part because of the perverse influence of modern statistics which assumes all kinds of things are normally distributed except for the minor detail that they aren’t. When they make the book into a movie, Carl Friedrich Gauss will be the villain (who should be played by Max Von Sydow). Events like 9/11, the collapse of Long-Term Capital Management and most wars are Black Swans. No one sees them coming, but in retrospect people manage to explain them.
The book is full of wide-ranging applications of his thesis, great asides and mildly misanthropic comments about businesspeople, anyone in finance, economists, particularly Nobel Prize winners, German philosophers, forecasters of any kind, opera fans and the French.
The core of the book is the distinction between Mediocristan and Extremistan. Mediocristan is the world of the normal distribution, where outliers are extremely rare. Many physical characteristics have a normal distribution, such as height or weight. In Mediocristan, it is not at all likely that an additional observation will impact the sum of all observations in any significant way. Extremistan is very different and is the domain of the power law distribution (think of the power law curve in The Long Tail except the Taleb is all about why the head is way more important than the tail because in the real world you don’t know whether you’ve observed the head of the head yet). An outlier observation can dwarf the sum of all previous observations, such as Bill Gates entering the room when you’re observing wealth. Big swathes of the real world, particularly social dynamics and informational goods, are in Extremistan, are not normally distributed and we treat them as Mediocristan at our peril.
The bulk of the book examines why we are so blind to Black Swans and gets into a fair amount of behavioral psychology like the earlier book. Not surprisingly, we tend to look for things that reaffirm our beliefs as opposed to contradict them; we’re good at constructing stories to explain things after the fact; we tend to ignore the silent evidence “of cemeteries” and focus disproportionately on the winners (think survivorship bias); assume the real world abides by clear and understandable rules; and we generally overestimate what we know and underestimate what we don’t.
The book is kind of a bummer in that he doesn’t have much of a prescription for how to survive and thrive in Extremistan:
“I care about the premises more than the theories, and I want to minimize reliance on the theories, stay light on my feet and reduce my surprises. I want to be broadly right rather than precisely wrong. Elegance in the theories is often indicative of Platonicity and weakness – it invites you to seek elegance for elegance’s sake. A theory is like medicine (or government): often useless, sometimes necessary, always self-serving, and on occasion lethal. So it needs to be used with care, moderation and close adult supervision.”
Basically, he attributes success to “undirected trial and error” and encourages you to maximize your exposure to as many positive Black Swans as possible. Better to be lucky than good:
“Capitalism is, amongst other things, the revitalization of the world thanks to the opportunity to be lucky.”
“Everything is transitory. Luck both made and unmade Carthage; it both made and unmade Rome.”
He applies his thinking to a variety of different realms with very intriguing results. As a former options trader, he basically denounces Modern Portfolio Theory as complete bunk, a castle built on shifting Gaussian sands. He asserts that a mere ten days over the last fifty years account for HALF of the market’s performance (I assume it to be true but will adopt his stance of skeptical empiricism in the absence of verifying it). Needless to say, that means some very fat tails. He also revels in the various explanations of the blow-up of Long-Term Capital Management (which Roger Lowenstein chronicles quite well in the succinct When Genius Failed) and needles the Nobel Prize winning economists who were involved at length. Taleb implied in an interview that his own portfolio is roughly 80% T-bills and 20% exposure to positive Black Swans with unlimited upside which sounds like venture capital of some form.
He arrives at a similar conclusion as Andy Kessler on globalization and division of labor. Don’t sweat the US’s trade deficit. That is just revenue: just look at the balance of profits (where the US runs a surplus). He believes the US has focused on scaleable businesses where your revenue is not limited by your number of labor hours, but rather those that involve creativity and are often winner-take-all in the global economy. We export jobs for the non-scaleable elements to others who are happy to be paid by the hour: “There is more money in designing a shoe than actually making it; Nike, Dell and Boeing can get paid for just thinking, organizing and leveraging their know-how and ideas while subcontracted factories in developing countries do the grunt work and engineers in cultured and mathematical states do the noncreative technical grind”.
He also looks at innovation. I’ve always believed that any successful technology has a strong element of serendipity in its adoption (standards body denizens hate it when you point this out and this would be a wonderful area to add up the “silent evidence” of failures) and he makes the same point, even using the word serendipity:
“If you think that the inventions we see around us came from someone sitting in a cubicle and concocting them according to a timetable, think again: almost everything of the moment is the product of serendipity.”
I’ll save a discussion of the role of Black Swans in Microsoft’s history for my oft-mentioned, but entirely un-started book.
In short, it is a great and thought-provoking read. It is rife with parenth
eticals and asides like the following that also make it entertaining:
“You can even include Frenchmen (but please, not too many out of consideration for the others in the group)…”
“Line up a thousand authors (or people begging to get published, but calling themselves authors instead of waiters)…”
“The person becomes more vulnerable to all manner of fads, such as astrology, superstitions, economics. and tarot-card reading.”
“They will probably take up, depending on their temperaments, bird-watching, Scrabble, piracy, or other pastimes.”
“Everyone has an idea of utopia. For many it means equality, universal justice, freedom from oppression, freedom from work (for some it may be the more modest, though no more attainable, society with commuter trains free of lawyers on cell phones).”
“Eventually, authors who are not often cited will drop out of the game by, say, going to work for the government (if they are of a gentle nature), or for the Mafia, or for a Wall Street firm (if they have a high level of hormones).”
“When you are employed, hence dependent on other people’s judgment, looking busy can help you claim responsibility for the results in a random environment. The appearance of busyness reinforces the perception of causality, of the link between results and ones’ role in them.”
“Being an executive does not require very developed frontal lobes, but rather a combination of charisma, a capacity to sustain boredom, and the ability to shallowly perform on harrying schedules. Add to these tasks the “duty” of attending opera performances.”
“Economics is the most insular of fields; it is the one that quotes least outside itself! Economics is perhaps the subject that currently has the highest number of philistine scholars — scholarship without erudition and natural curiosity can close your mind and lead to the fragmentation of disciplines.”
“Optimization is a case of sterile modeling… It had no practical (or even theoretical) use, and so it became principally a competition for academic positions, a way to make people compete with mathematical muscle. It kept Platonified economists out of the bars, solving equations at night.”
“Alas, it turns out that it was [Paul] Samuelson and most of his followers who did not know much math, or did not know how to use what math they knew, how to apply it to reality. They only knew enough math to be blinded by it.”