Power Tail Distributions
When we used a Pareto distribution for the continuous double auction model, we did not develop any rationale or theory about how such distributions might occur in financial markets. William Reed, a mathematician, at the University of Victoria (see reference page) has developed a distribution which he calls the double Pareto lognormal distribution which may be a better representation of the distributions in order books, but more research is needed on this idea.
The simplest power tail distribution is the Pareto distribution; it is essentially only a tail and a defined starting point, before which the value is zero. The density function for a Pareto distribution that starts at one and its plot are below. α is the tail exponent.
It is easy enough to generate Pareto random variables from a uniform random variable, because the distribution function has a simple formula which can be solved for x and p(x) is then a uniform random variable.
But that doesn't give any insight as to how a Pareto distribution might arise in financial markets. A Pareto random variable starting at one, can also be generated by taking the exponent (base e) of an Exponential random variable. The Exponential distribution has a light tail; the mean and variance exist, but that is not true for its exponent when the parameter λ is less than 2 for the variance or 1 for the mean.
Here is the proof using characteristic functions. The characteristic function of the exponent of an exponential random variable is:
This is the characteristic function of the ParetoDistribution[1, λ] as can be seen by doing the inversion of the Fourier Transform to get the density:
Exponential distributions are often used to characterize waiting times. In the case of markets it might be a waiting time for a transaction, but if the value of the asset is appreciating exponentially while waiting, it is easy to see how prices might have some tendency toward a Pareto distribution. In the next pages we explore some of the other distributions that Dr. Reed has described.
© Copyright 2007 mathestate Fri 28 Dec 2007