Asymptotic approximations for the distribution of the product of correlated normal random variables

We obtain asymptotic approximations for the probability density function of the product of two correlated normal random variables with non-zero means and arbitrary variances. As a consequence, we deduce asymptotic approximations for the tail probabilities and quantile functions of this distribution, as well as an asymptotic approximation for the widely used risk measures value at risk and tail value at risk.

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Publication Details

Journal
Journal of Mathematical Analysis and Applications
Published
2024-11-05
DOI
https://doi.org/10.1016/j.jmaa.2024.128987
Citations
4
Primary Topic
Probability and Risk Models
Type
article
Field-Weighted Citation Impact
1.96

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article

Asymptotic approximations for the distribution of the product of correlated normal random variables

Robert E. Gaunt, Zixin Ye
4 citations
Journal of Mathematical Analysis and Applications
Probability and Risk Models
1.96
article

Asymptotic approximations for the distribution of the product of correlated normal random variables

Robert E. Gaunt, Zixin Ye
article en
4 citations

Abstract

We obtain asymptotic approximations for the probability density function of the product of two correlated normal random variables with non-zero means and arbitrary variances. As a consequence, we deduce asymptotic approximations for the tail probabilities and quantile functions of this distribution, as well as an asymptotic approximation for the widely used risk measures value at risk and tail value at risk.

Journal of Mathematical Analysis and ApplicationsVol. 543(2)
University of Manchester (GB)
University of Manchester, Engineering and Physical Sciences Research Council
Openalex Percentile: Top 12%
Probability and Risk Models
1.96
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