Modeling financial data with stable distributions

By John P. Nolan. 2003

127 citations recorded by the source corpus.

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 dierent 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.

Subfields: Economics and Econometrics, Finance, Management Science and Operations Research

View Paper: https://www.semanticscholar.org/paper/678197c29eedcc6b446561969da453469a53c332

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Economics and Econometrics

1. Ayoub Ammy-Driss
2. Matthieu Garcin

In Finance

1. Ayoub Ammy-Driss
2. Matthieu Garcin

In Management Science and Operations Research

1. Ayoub Ammy-Driss
2. Matthieu Garcin

Citations in the corpus

• Efficiency of the financial markets during the COVID-19 crisis: Time-varying parameters of fractional stable dynamics (2020, background): “For this reason, it has been widely invoked in signal processing [69, 32, 33], with applications for example in medicine [68, 71] or in finance [48, 60, 29].”