Modeling Financial Data with Stable Distributions
John P. Nolan Department of Mathematics and Statistics, American University
Abstract
Stable distributions are a class of probability distributions that allow heavy tails and skewness. In addition to theoretical reasons for using stable laws, they are a rich family that can accurately model different kinds of financial data. We review the basic facts, describe programs that make it practical to use stable distributions, and give examples of these distributions in finance. A non-technical introduction to multivariate stable laws is also given.
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