The Black Swan

In 1982, large American banks lost all their past earnings, about everything they ever made in the history of American banking. Why? They have been lending money to South and Central American countries that all defaulted at the same time.

Larry Page and Sergey Brin studied computer science at Stanford University. They came up with a superior way of searching information on the internet. They cofounded the company Google. On one occasion they tried selling the company for $1 million. The buyer refused telling that the price was too high. As of today Google controls 66.7% of the search market and the company is valued at $355 billion.

Is there any relation between the two events? Both are black swan events.

In the book The Black Swan – Taleb tells that black swan event has 3 attributes

1. It is an outlier, as it lies outside the realm of regular expectations, because nothing in the past can convincingly point to its possibility.
2. It carries an extreme impact. The impact can be both positive or negative. In the bank example it had a negative impact and it is called negative black swan. In the Google example it had a positive impact and it is called positive black swan.
3. In spite of its outlier status, human nature makes us concoct explanations for its occurrence after the fact, making it explainable and predictable.

Why should we care about black swans?

A small number of Black Swans explain 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.

I encountered black swans very early in my life.

When I was 15, I lost my mother and exactly after 6 months my father had a brain hemorrhage. I encountered two negative black swans in quick succession. It changed the fate of my life. I had to discontinue my studies and took up a government job when I was 18. I worked there for almost 6 years.

While I was working for the government, I took some classes on computer programming. I got hooked on to it immediately and spent most of my time learning it. At the same time internet became popular and I got a job as a programmer in the software industry. I was lucky to encounter a positive black swan.

Look at your life there will be very few events that would have decided your course of action.

Where do we find black swans?

Imagine a software consultant who charges $50 per hour and works 40 hours per week. He will make $2000 in one week. In one year he will make $100,000. Even if he works 80 hours per week his income per year will be $200,000. He cannot work beyond so many hours per day and hence his income cannot grow beyond a certain limit. This profession is not scalable. Taleb refers to these non-scalable environments as mediocristan.

JK Rowling is the author of the famous Harry Potter books. Her last book Harry Potter and the Deathly Hallows, sold eleven million copies. She spent time to write the book only once and did not spend any additional time for selling the second, third or the eleventh million copy. This profession is scalable. Taleb refers to these scalable environments as extremistan.

Black swans proliferate in extremistan environments. You can learn how the world works by studying the black swan events. Some of the black swans that I can think of are: Steve Jobs, iPhone, Internet, 2008 financial crisis, Long Term Capital Management, Warren Buffett and Facebook. 

Take a look at some of the differences between mediocristan and extremistan.

Mediocristan	Extremistan
Nonscalable	Scalable
Events are distributed according to the bell curve	Events are distributed according to the power laws
Winner get a small segment of the total pie	Winner-take-almost-all effects
The most typical member is medicore	The most “typical” is either gaint or dwarf, i.e., there is no typical member
Easy to predict from what you see and extend to what you do not see	Hard to predict from past information
Examples: height, weight, income for a baker, car accidents, mortality rates	Examples: wealth, income, book sales per author, populations of cities, uses of words in a vocabulary, sizes of companies, stock ownership.

Can we predict black swans?

Black swans cannot be predicted. You can only know about it after it has happened. We humans are not very good at predictions.

Sydney Opera house was supposed to open in early 1963 at a cost of AU$ 7 million. It finally opened a decade later and it costed AU$ 104 million.

In January 2004, US government department was forecasting the price of oil for twenty-five years later at $27 a barrel, slightly higher than what it was at that time. Six months later in June 2004 the oil barrel doubled in price.

In 1999 Google founders Larry Page and Sergey Brin tried selling the company for $1 million to Excite. But the Excite CEO George Bell rejected the $1 million offer. Vinod Khosla talked the duo down to $750,000. But Bell still rejected that. No one had a clue that Google would become the internet search giant.

Thomas Watson, the founder of IBM, once predicted that there would be no need for more than just a handful of computers. I am writing this blog using my computer.

Michael Dell founder of Dell Computers, when asked what he’d do with Apple if he were in Jobs’ shoes, Dell said: What would I do? I’d shut it down and give the money back to the shareholders. As of this writing Apple is valued at $491.22 billion.

From all this it should be very clear that we cannot predict black swans.

Most of the positive black swans came out of 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… In other words, you find something you are not looking for and it changes the world, while wondering after its discovery why it “took so long” to arrive at something so obvious. No journalist was present when the wheel was invented, but I am ready to bet that people did not just embark on the project of inventing the wheel and then complete it according to a time table.

Be Prepared

Taleb advises us to avoid exposure to negative black swans and seek exposure to positive ones.

Long Term Capital Management (LTCM) was a hedge fund management firm run by some of the smartest people on the planet. At the beginning of 1998, the firm had equity of $4.72 billion and had borrowed over $124.5 billion with assets of around $129 billion, for a debt to equity ratio of over 25 to 1. It went bankrupt during the 1998 Russian financial crisis.

The take away lesson for me is to avoid excess debt in life. This way I can avoid exposure to few negative black swans.

Buffett talks about LTCM 

We need to increase our exposure to places where black swans proliferate. Here is one advice from Taleb

Remember that positive Black Swans have a necessary first step: you need to be exposed to them. Many people do not realize that they are getting a lucky break in life when they get it. If big publisher (or a big art dealer or a movie executive or a hotshot banker or a big thinker) suggests an appointment, cancel anything you have planned: you may never see such a window open up again. I am sometimes shocked at how little people realize that these opportunities do not grow on trees. Collect as many free non-lottery tickets (those with open-ended payoffs) as you can, and, once they start paying off, do not discard them. Word hard, not in grunt work, but in chasing such opportunities and maximizing exposure to them. This makes living in big cities invaluable because you increase the odds of serendipitous encounters – you gain exposure to the envelope of serendipity.

Some of the business with positive black swans are movies, some segments of publishing, scientific research, and venture capital.

Venture capitalists get exposed to lots of black swans. They fund a lot of small startups. Most of them will fail but some of them turn out to be black swans like Facebook which make a lot of money. They are in the business of losing pennies to gain dollars. YCombinator a company founded by Paul Graham which  does seed funding for the startups. They make small investments (rarely more than $20,000) in return for small stakes in the companies we fund (usually 2-10%). It is a terrific idea.

Most of us will not have a lot of money to be a venture capitalist. What should we do? If I were a software engineer I would try to work for startups instead of big corporations. Why?  You will get your paycheck in startups with a downside risk of losing the job if the startup does not go anywhere. In that case you can find another job. But if the startup is successful the upside potential is huge. The main idea is to position yourself in situations where favorable consequences are much larger than unfavorable ones. There will be volatility in the process but it is not risky.

If you are a retail investor Prof. Sanjay Bakshi explains how to use positive black swans in your favor.

Taleb’s book The Black Swan is a fantastic read and I throughly enjoyed reading it.