I just finished reading the excellent book
The Black Swan: The Impact of the Highly Improbable
and he he has a graph that shows that if you were a long term investor in the S&P 500 and you (someone) missed out on the days with the 10 largest returns that your net would be considerably different.
I’m following around with trying to reproduce his results and well, this is just a kind of note of a work n progress.
According to my calculations these are the days of the largest gains and loses in the S&P:
This chart tries to show the frequency of all % changes, where the horizontal access is %change of the S&P 500 from -30% to +30%, and the vertical access is of course frequency, namely the number of days the index changed by that much. It’s hard to see if the graph is centered at zero, and at appears symmetric, but not really like a bell curve…so it’s probably time to get another charting tool so I can better get a handle on this data:
I’m using the nice Python utility pyq to retrieve the data, and it in turns calls into Yahoo Finance (see this page for historical data on ^GSPC, which is the symbol for S&P 500).
As an aside, I discovered Swivel, which seems to be an interesting social data analysis site, so I’ll probably experiment more with them.
