A Few Lessons from The Black Swan

By | November 18, 2013

 

As promised, here is the next in the series of me reviewing Taleb’s books. This was my third reading of the book and one that took me a lot longer to get through. Also to be honest, I didn’t enjoy it as much as I enjoyed his first book Fooled By Randomness. Even then, the book has a lot of things you can learn, and in all honesty I think it does have a central thesis that makes you see the world differently. I am not going to talk about his writing style, or the fact that this book does seem to have some inconsistencies, but try and distill some of the big picture items that one can use and apply. (For reviews that highlight some inconsistencies, I suggest you read The Black Swan – Praise and Criticism and Revenge of the White Swan by Robert Lund)

The book’s central thesis is that in order to understand history and events of significance, you need to understand what Taleb calls Black Swan events – i.e. events that are found at the tails of statistical distributions. These black swan events are outliers and by definition are unpredictable. History and all social sciences (including finance and economics) are shaped not by events around the mean, but rather by these events that lie in the tails of the distributions.

outliers and black swan events

For an event to be categorized as a Black Swan event, it must meet the following three criteria:

  1. It is an outlier – i.e. lies outside the boundaries of the mean.
  2. It carries an extreme impact
  3. You can always explain the event a posteriori (as opposed to a priori)

What can we learn from The Black Swan?

  • Scalable professions – Very early on in the book, Taleb talks about something that I find very interesting. He says that this was the most important piece of advice he received, but which was

…in retrospect bad, but was also paradoxically, the most consequential…

Scalable professions are those that let you add zeroes to your output, with zero or little effort. These professions can be scaled very easily. There are quite a few examples in the book but the ones I like are the following:

If you are a prostitute, you work by the hour and are (generally) paid by the hour. Furthermore, your presence is necessary for the service you provide. If you open a fancy restaurant, you will at best steadily fill up the room. In these professions, no matter how highly paid, your income is subject to gravity. Your revenue depends on your continuous efforts more than the quality of your decisions. Moreover, this kind of work is largely predictable: it will vary, but not to the point of making the income of a single day more significant than that of the rest of your life.

If you are an idea person, you do not have to work hard, only think intensely. You do the same work whether you produce a hundred units or a thousand. In quant trading, the same amount of work is involved in buying a hundred shares as in buying a hundred thousand, or even a million. It is the same phone call, the same computation, the same legal document, the same expenditure of brain cells, the same effort in verifying that the transaction is right. Furthermore, you can work from your bathtub or from a bar in Rome. You can use leverage as a replacement for work!

  • Build an antilibrary – i.e. don’t feel bad about the books you haven’t read in your library

Read books are far less valuable than unread ones. The library should contain as much of what you do not know as your financial means, mortgage rates and the currently tight real-estate market allow you to put there. You will accumulate more knowledge and more books as you grow older, and the growing number of unread books on the shelves will look at you menacingly. Indeed, the more you know, the larger the rows of unread books. Let us call this collection of unread books an antilibrary.

I couldn’t have said it better. This is my personal philosophy when it comes to spending money on books. Everything else I am much more judicious about, but books are an indulgence for me. Besides, reading the is only way you can get smarter!

  • Mediocristan vs Extremistan - Everything of importance belongs to the world of Extremistan, but our models are based on the assumption that we live in mediocristan. What is the difference?

When your sample is large, no single instance will significantly change the aggregate or total. The largest observation will remain impressive, but eventually insignificant, to the sum.

In Extremistan, inequalities are such that one single observation can dispropotionately, impact the aggregate, or the total.

Weight, height and calorie consumption belong to Mediocristan. Wealth belongs to Extremistan. I will expand on this topic in a later post.

  • The Problem of Induction – also known as the Turkey Problem

Induction is being able to logically draw general conclusions from observing specific instances. (Deduction is the symmetric opposite – being able to draw specific conclusions from observing the general). Taleb frames this philosophical question as:

How can we know the future, given knowledge of the past; or more generally how can we figure out properties of the (infinite) unknown base on the (finite) known?

Consider a turkey that a butcher feeds every day. Every single day that it gets fed, the Turkey is under the impression that the butcher is looking out for its best interest and that humans in general are kind hearted souls. The day before Thanksgiving, something unexpected will happen to the turkey.

More generally, just because something has occurred over the past n number of days or time periods, doesn’t necessarily mean that it will occur on the n+1 time period.

Something has worked in the past, until – well, it unexpectedly no longer does, and what we have learned from the past turns out to be at best irrelevant or false, at worst viciously misleading.

  • The Confirmation Bias – this is the natural tendency for humans to seek out instances that corroborate or lend positive validity to our previously held assumptions or ideas.You will always seek out information that will validate your existing beliefs or hypotheses. The confirmation bias will push you to make decisions that may blow up in your face. For a more detailed explanation check out Confirmation Bias on FarnamStreet.
  • The Narrative Fallacy -

The narrative fallacy addresses our limited ability to look at sequences of facts without weaving an explanation into them, or, equivalently, forcing a logical link, an arrow of relationship, upon them. Explanations bind facts together. They make them all the more easily remembered; they help them make more sense. Where this propensity can go wrong is when it increases our impression of understanding.

There are two reasons why we fall victim to this fallacy. The first being that information is very expensive to find and obtain. The second being that the same information is very expensive to store. By weaving a story, you are in essence reducing the amount of space the same piece of information takes up as opposed to having random pieces of facts floating around in your brain.

the same condition that makes us simplify pushes us to think that the world is less random than it actually is.

How do we avoid the narrative fallacy?

    • by favoring experimentation over storytelling
    • by predicting and keeping a tally of predictions
    • convince with a story that conveys the right message
  • The Ludic Fallacy – Ludic comes from ludus, Latin for games. This is very similar to understanding the difference between risk and uncertainty. Simply put, risk is what you can measure, uncertainty is what you can’t.

The casino is the only human venture I know where the probabilities are known, Gaussian (i.e. bell-curve), and almost computable.

…in real life you do not know the odds; you need to discover them, and the sources of uncertainty are not defined.

Taleb’s point is that predictive models tend to favor mathematical purity over usefulness and fail to account for all variables.

  • The Barbell Strategy -

If you know that you are vulnerable to prediction errors, and if you accept that most “risk measures” are flawed, because of the Black Swan, then your strategy is to be hyperconservative and hyperaggressive as you can be instead of being mildly aggressive or conservative. Instead of putting your money in “medium risk” investments, you need to put a portion, say 85 to 90 percent, in extremely safe instruments, like Treasury bills – as safe a class of instruments as you can manage to find on this planet. The remaining 10 to 15 percent you put in extremely speculative bets, as leveraged as possible (like options), preferably venture capital-style portfolios. That way you do not depend on errors of risk management; no Black Swan can hurt you at all, beyond your “floor”, the nest egg you have in maximally safe investments. Or, equivalently, you can have a speculative portfolio and insure it against losses of more than, say, 15 percent. You are “clipping” your incomputable risk, the one that is harmful to you. Instead of having medium risk, you have high risk on one side and no risk on the other. The average will be medium risk but constitutes a positive exposure to the Black Swan.

For more on where this came from, I suggest you read The Black Swan: The Impact of the Highly Improbable.


Overall: ****
Learning and Applicability: ****

Overall Rating:
***** – Loved it, devoured it, recommended it to a friend, now in my library.
****  - Loved it, devoured it, put it away in my library.
***   – Read it, returned it to the library.
**    - Wasted 3 hours.
*     – Couldn’t get past the first chapter.

Learning and Applicability Rating:
***** – Learn’t to see the world in a different light all together, knowledge can be applied in everyday life, taught me stuff I never knew.
****  - Learn’t to see the world in a different light somewhat, most of the knowledge can be applied, taught me a few things I didn’t know.
***   – Built upon some things I knew, but nothing ground breaking. Can’t really apply the knowledge to everyday life.
**    - Learn’t absolutely nothing useful.
*     – The sun goes around the earth? What?

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