Absolute moments of the variance-gamma distribution

We obtain exact formulas for the absolute raw and central moments of the variance-gamma distribution, as infinite series involving the modified Bessel function of the second kind and the modified Lommel function of the first kind. When the skewness parameter is equal to zero (the symmetric variance-gamma distribution), the infinite series reduces to a single term. Moreover, for the case that the shape parameter is a half-integer (in our parameterisation of the variance-gamma distribution), we obtain a closed-form expression for the absolute moments in terms of confluent hypergeometric functions. As a consequence, we deduce new exact formulas for the absolute raw and central moments of the asymmetric Laplace distribution and the product of two correlated zero mean normal random variables, and more generally the sum of independent copies of such random variables.

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Publication Details

Journal
Journal of Mathematical Analysis and Applications
Published
2024-09-10
DOI
https://doi.org/10.1016/j.jmaa.2024.128861
Citations
3
Primary Topic
Stochastic processes and financial applications
Type
article
Field-Weighted Citation Impact
1.62

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article

Absolute moments of the variance-gamma distribution

Robert E. Gaunt
3 citations
Journal of Mathematical Analysis and Applications
Stochastic processes and financial applications
1.62
article

Absolute moments of the variance-gamma distribution

Robert E. Gaunt
article en
3 citations

Abstract

We obtain exact formulas for the absolute raw and central moments of the variance-gamma distribution, as infinite series involving the modified Bessel function of the second kind and the modified Lommel function of the first kind. When the skewness parameter is equal to zero (the symmetric variance-gamma distribution), the infinite series reduces to a single term. Moreover, for the case that the shape parameter is a half-integer (in our parameterisation of the variance-gamma distribution), we obtain a closed-form expression for the absolute moments in terms of confluent hypergeometric functions. As a consequence, we deduce new exact formulas for the absolute raw and central moments of the asymmetric Laplace distribution and the product of two correlated zero mean normal random variables, and more generally the sum of independent copies of such random variables.

Journal of Mathematical Analysis and ApplicationsVol. 543(1)
University of Manchester (GB)
Engineering and Physical Sciences Research Council
Reduced inequalities
Openalex Percentile: Top 16%
Stochastic processes and financial applications
1.62
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Absolute moments of the variance-gamma distribution — Robert E. Gaunt · Journal of Mathematical Analysis and Applications (2024) | TGRS Research Map | TGRS