I finally managed to finish reading the much hyped book by Mr. Taleb - "Black swans".
I had not known that getting a Job would be such a big deal if one was graduating from (supposedly) one of India's top school. Nevertheless the last few months kept me very busy with all the "preparations" for the Job interviews, learning how to be "The guy" that the hiring firm wants!
On-to the book now -
Black swans and the G.I.F -
It was an interesting read for me. It had a lot of grounding in things that I thought were intuitive but ignored by us lesser mortals in our daily lives. On of the few things that I will remember from the book after an year would be that way he denounced the ubiquitous "Gaussian Bell Curve" as a "Great Intellectual Fraud". His reasoning is as follows -
-- The Gaussian distribution is (sadly) such that it does not allow for extreme events to happen ( more technically - the odds of an extreme event are very low). However, our lives are shaped by such extreme events - be it hurricanes, stock market crashes or un-foreseen inventions. Why then do we use the "bell curve" to predict the future ? Worse still we justify such shocks and never learn the basic fact that we cannot predict! The world would be a much better place if we could learn to exploit uncertainty, embrace it in it's wildest form. Interestingly, such events have a black (unexpected) connotation to them - Black Thursday, Black Monday. How ignorant can we humans be?
He has come down heavily on the Nobel Laureates such as Merton-Scholes for being a phony - making up theories that have assumptions conjured up by a guy from some dream-land, far fetched from reality. I agree a lot with this point. Many of our theories today are based on un-realistic assumptions (read "Gauss bell curve"), but the question is - Can we do better? Since I know a bit about financial markets (I think!) I'll take an example from that domain -
Say you invested in Microsoft in 1999. The stock was doing better that good and you see good returns. The black swan is the "Dot-com crash". It is true that not many people saw this improbable event and it had a high (negative) impact on many people. But two questions arise -
1. Do we learn ? I think we (read some good economists) do. A few good people were able to predict the housing crisis. (Eg. "Has financial development made the world riskier" - R. Rajan). We do realise that such things exist and we can possibly do something about them. Maybe this does not extend this to other domains but the idea is certainly there.
2. Do we stop going out because on some bad day we might be killed in a road accident or struck by thunderbolts? No ! Black swans are a part of life (as he says). Whether he is concerned about us being ignorant about it or being oblivious to it is unclear.
"Why we don't learn that we don't learn"
This is another interesting chapter that further exemplifies our ignorance towards events. The so-called pundits make predictions, fail miserably and then justify it. They are worse off than a cab driver who has the guts to say "I don't know" when asked about the weather tomorrow.
Take away point - It is as important (if not more) to know what you don't/cannot know (and not be foolish about it) as it is to know things and make predictions.
"So what to do about it?"
Almost all the interesting stuff happens in the Extremistan world - where the improbable (one freak occurrence) can invalidate your whole theory, mess up your predictions. We still tend to think that we are in the Mediocristan world - where things "average" out.
Barbell strategy - "Hedge yourself from such black swans by investing your money/time/energy in low risk places. Assess the Black swan - if it has a possible positive outcome (shorting something and it crashes - George Soros style) invest 10-15 % of your money in it. (I apologize for the proclivity for the financial markets) Otherwise, stay away from it. Financial market analysts know about markets as much as a cab driver but somehow people (foolishly) put a lot of faith in them! He recommends the use of "Fractals", demonstrating beautifully how they can give you hints about black swans and make them grey.
Last piece of advise - Be a sceptic. This was one of the key take-away's for me. If you have a theory, do not discard the outliers. Search for the one data point that can screw up your theory (We usually do it the other way round - confirmation bias is ingrained in us). Don't fall for the Ludic fallacy (read the book to know what it means!).
P.S - Next time someone says - "Dude! This follows the normal distribution, have a good laugh at the fool. "
It was an interesting read for me. It had a lot of grounding in things that I thought were intuitive but ignored by us lesser mortals in our daily lives. On of the few things that I will remember from the book after an year would be that way he denounced the ubiquitous "Gaussian Bell Curve" as a "Great Intellectual Fraud". His reasoning is as follows -
-- The Gaussian distribution is (sadly) such that it does not allow for extreme events to happen ( more technically - the odds of an extreme event are very low). However, our lives are shaped by such extreme events - be it hurricanes, stock market crashes or un-foreseen inventions. Why then do we use the "bell curve" to predict the future ? Worse still we justify such shocks and never learn the basic fact that we cannot predict! The world would be a much better place if we could learn to exploit uncertainty, embrace it in it's wildest form. Interestingly, such events have a black (unexpected) connotation to them - Black Thursday, Black Monday. How ignorant can we humans be?
He has come down heavily on the Nobel Laureates such as Merton-Scholes for being a phony - making up theories that have assumptions conjured up by a guy from some dream-land, far fetched from reality. I agree a lot with this point. Many of our theories today are based on un-realistic assumptions (read "Gauss bell curve"), but the question is - Can we do better? Since I know a bit about financial markets (I think!) I'll take an example from that domain -
Say you invested in Microsoft in 1999. The stock was doing better that good and you see good returns. The black swan is the "Dot-com crash". It is true that not many people saw this improbable event and it had a high (negative) impact on many people. But two questions arise -
1. Do we learn ? I think we (read some good economists) do. A few good people were able to predict the housing crisis. (Eg. "Has financial development made the world riskier" - R. Rajan). We do realise that such things exist and we can possibly do something about them. Maybe this does not extend this to other domains but the idea is certainly there.
2. Do we stop going out because on some bad day we might be killed in a road accident or struck by thunderbolts? No ! Black swans are a part of life (as he says). Whether he is concerned about us being ignorant about it or being oblivious to it is unclear.
"Why we don't learn that we don't learn"
This is another interesting chapter that further exemplifies our ignorance towards events. The so-called pundits make predictions, fail miserably and then justify it. They are worse off than a cab driver who has the guts to say "I don't know" when asked about the weather tomorrow.
Take away point - It is as important (if not more) to know what you don't/cannot know (and not be foolish about it) as it is to know things and make predictions.
"So what to do about it?"
Almost all the interesting stuff happens in the Extremistan world - where the improbable (one freak occurrence) can invalidate your whole theory, mess up your predictions. We still tend to think that we are in the Mediocristan world - where things "average" out.
Barbell strategy - "Hedge yourself from such black swans by investing your money/time/energy in low risk places. Assess the Black swan - if it has a possible positive outcome (shorting something and it crashes - George Soros style) invest 10-15 % of your money in it. (I apologize for the proclivity for the financial markets) Otherwise, stay away from it. Financial market analysts know about markets as much as a cab driver but somehow people (foolishly) put a lot of faith in them! He recommends the use of "Fractals", demonstrating beautifully how they can give you hints about black swans and make them grey.
Last piece of advise - Be a sceptic. This was one of the key take-away's for me. If you have a theory, do not discard the outliers. Search for the one data point that can screw up your theory (We usually do it the other way round - confirmation bias is ingrained in us). Don't fall for the Ludic fallacy (read the book to know what it means!).
P.S - Next time someone says - "Dude! This follows the normal distribution, have a good laugh at the fool. "
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