Tuesday, May 1, 2012

"Credit Suisse: Making Fat Tails Work for You"

From All About Alpha:
Both theory and empirical evidence on the success of certain “modified risk techniques” show that they can do what they are designed to do. They can accommodate fat tail events and diversify a portfolio’s sources of return.

That is the gist of a Credit Suisse white paper prepared by Yogi Thambiah and Nicolo’ Foscari.
The paper is entitled, “New Normal Investing: Is the (Fat) Tail Wagging Your Portfolio?” a title that neatly encapsulates two bits of finance jargon. First, there is the phrase “new normal,” coined by PIMCO in 2009, to express the view that investors and managers shouldn’t wait for any return of the good-old-days of the boom in real estate and its derivatives. They should, rather, accustom themselves to the world that the bust-ups of 2007-08 have created.

The new normal, on Thambiah’s and Foscari’s account, includes an enhanced role by central banks, implementing monetary policies through open market operations, closer interconnections of banking institutions worldwide, much painful de-leveraging, and persistently high levels of unemployment.

The Tails on a Bell Curve
The second buzz phrase, “fat tail,” is drawn from the world of statistics, and plays off the familiar Gaussian distribution, or “bell curve.”

In this distribution, more than 68 percent of outcomes will be found with one standard deviation of the mean, and 95 percent of the outcomes will be found within two standard deviations. The “tails,” the bits of the curve at or outside three standard deviations, are then quite skinny.

But finance is not a Gaussian world. Extreme events simply occur more frequently than they would in such a world. It isn’t quite right to say that in the ‘old normal’ distribution was Gaussian and in the ‘new normal’ it isn’t. The distribution of outcomes in finance may never have been Gaussian. They certainly didn’t seem Gaussian in October 1987 for example. But various models and equations in modern finance theory incorporate Gaussian distribution at least as a matter of convenience....MORE