TITLE

Is Non-normal Normal?

AUTHOR(S)
Connelly, Thomas J.
PUB. DATE
August 1998
SOURCE
Journal of Financial Planning;Aug1998, Vol. 11 Issue 4, p30
SOURCE TYPE
Academic Journal
DOC. TYPE
Article
ABSTRACT
This column focuses on some of the underlying assumptions regarding the models used by financial planners and points out that some of the important underlying concerns are still far from resolved. Models are abstractions of reality to varying degrees, based on theory and empirical observation. When the relationship between cause and effect is uncertain, because of the number of variables involved and complex interrelationships between variables, models of stochastic processes are often used. In 1900, Louis Bachelier defended a doctoral dissertation titled The Theory of Speculation. It was the formulation of a model that attempted to describe the price fluctuations of French government bonds and options on the Paris Exchange. Bachelier postulated that the changes in the logarithms of bond prices were normally distributed by invoking the central limit theorem. Benoit Mandelbrot searched for a probability distribution that fit the price change data better than the normal distribution by studying changes in the logarithms of cotton prices. Planners should view their current statistical tool box with at least some skepticism, and realize that the current tool set, including least squares regressions, optimization, Monte Carlo analysis specifying the wrong probability distribution, to name a few, may be giving misleading results if the proponents of the stable Levy hypothesis turn out to be correct. A model specifying infinite variance would certainly affect option pricing, since a sizable component of option prices depends on volatility.
ACCESSION #
988337

 

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