Marc the millionarire on Park Aveanue

I was reading the book "Fooled By Randomness" by Nassim Nicholas Taleb. In one of the sections called "Too Many Millionaires Next Door" he tells the story of Marc a Lawyer in NewYork city. I have rephrased the section below:

Mark is a lawyer in Newyork city and stays in Manhattan along with his wife. He is an intelligent lawyer who studied in harvard college and did his law from the Yale Law school. In his late 40s and earning about $500,000 he was a well settled man. His office life was hectic. He would work till 9:30 on many days and sometimes you would find him in the office even at midnight. Because of the fatigue his weekends would be lost in recuparating from the excessive work loads. He had become a partner within 7 years of his initial working years. All this hardwork left his wife frustrated and she left him.

He started dating janet, his paralegal. Later on he married her and bought an appartment on Park Avenue. Janet used to meet people from the neighbourhood manhattan houses probably once a month during the parents meet. Because of her homely girl appearance she would get snubbed by some people. She would even get jealous looking at the huge diamond ring some other lady would be wearing. Then she would wonder why her husband, even though was a yale graduate, was not earning enough to buy her all these itesms. Isn't he smart ? Why was Ronald Something whose wife would not even look at janet, worth so many millions where as her husband who was a yale graduate did not have enough savings ?

Now Janet has a feeling that her husband is a failure. But her comarision is wrong and the conclusion drawn (i.e. her husband is a failure) is totally baseless. Because she is using a wrong distribution to derive a rank.

Now compared to the General US population, Mark has done very well, better than 99.5% of his compatriots. Compared to his other harward friends he did better than 90% of them. Compared to his batchmates from Yale Law school his did better than 60% of them. BUT compared to his neighbours he is at the bottom...
why ? Because he chose to live on Park Aveanue where every neighbour is successful. But Janet did not consider the failure cases. If a guy was a failure he would not be living on the Park aveanue in the first place. So Janets sample space consisted only of successful people as living on park aveanue will not give you failures for comparision and hence she felt Marc is a failure. This lead to considerable emotional distress. Here she has married an extremely successful man but all she can see is failure in comparision with her neighbours.

Janets vision is myopic. and the sample space of comparision is wrong. This sample space is a small collection of extremely successful people in the city and comparing among them to find out your standing and being sad that marc is a failure would be doing injustice to Marc.

Moral:
When you compare youeself with others and feel you are a failure because you seem to be at the bottom of the sample space of your comparision. Just cross check your sample space. You might have actually chosen a worng set of guys/ladies to compare yourself with.

In janets case it would be better if she moves from the park aveanue and move into a different neighbourhood.

Removing spikes from samples

I am reading a book called Fooled by Randomness by a derivatives trader Nassim Nicholas Taleb.

In one of the chapters he mentions about how sampling and removal of spikes from the samples can lead to improper interpretation of facts...

In the section called Symmerty and Science on Page 105, he explains how most people remove the highest and lowest values while calculating averages. Below I summarize his arguement

Example 1:
A professor would remove the highest and lowest marks as spikes and uses only the rest of the values to find an average of class marks. The author feels it is an unsound practice.

Example 2:
A whether forcaster removes the spikes in the temperature while calculating the average temperature assuming that these are rare events and would not occur again.
Suppose somebody uses this average temperature to forcast global warming and the rate of melting of polar ice caps, the guy might horribly go wrong because while calculating the average temperature, the spikes were ignored as one off event. But this one off event could have caused disproportionate melting of ice. By ignoring this spike in temperature you ignored the irreversible affect this specific temperature rise could have caused on the ice caps.

Example 3:
He uses the above two arguements to nail the stock/derivatives markets forcasters and says:
I quote
"So people in finance borrow the technique and ignore infrequent events, not noticing that the effect of a rare event can bankrupt a company"
So such events although rare, brings large consequencs that cannot be just ignored"
unquote

A recent example of one such thing that immediately comes to my mind is the subprime crisis. In the history of Baer Sterns They might have made so many intelligent investments, stratergic buyouts. But Subprime Crisis brought the investment bank on it knees. So one rare event crippled the whole bank. If you were to remove this one event from the history of Bear Sterns and look at the performance of Baer Sterns you would feel that it is an excellent investment company... Then why on earth did it crash from close to $100 to $2 !!