Right-tail asymptotics for products of independent normal random variables

Fuente: arXiv
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Auteurs principaux: Chvoinikov, Džiugas, Šiaulys, Jonas
Format: Preprint
Publié: 2026
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author Chvoinikov, Džiugas
Šiaulys, Jonas
author_facet Chvoinikov, Džiugas
Šiaulys, Jonas
contents Let $X_1,\dots,X_n$ be independent normal random variables with $X_i\sim N(μ_i,σ_i^2)$, and set $Z=\prod_{i=1}^n X_i$. We derive asymptotic approximations for the right tail probability $\mathbb{P}(Z>x)$ as $x\to\infty$. When at least one mean is nonzero, the asymptotic formula remains explicit and involves a finite multiplicative factor arising from admissible sign patterns (reflecting the different ways the product can be positive); it includes an explicit first relative correction term of order $x^{-1/n}$, with remaining relative error $O(x^{-2/n})$. The proof uses a boundary saddle-point/Laplace method: first a multidimensional Laplace approximation near the boundary saddle, then a one-dimensional endpoint Laplace approximation.
format Preprint
id arxiv_https___arxiv_org_abs_2603_08570
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle Right-tail asymptotics for products of independent normal random variables
Chvoinikov, Džiugas
Šiaulys, Jonas
Probability
Let $X_1,\dots,X_n$ be independent normal random variables with $X_i\sim N(μ_i,σ_i^2)$, and set $Z=\prod_{i=1}^n X_i$. We derive asymptotic approximations for the right tail probability $\mathbb{P}(Z>x)$ as $x\to\infty$. When at least one mean is nonzero, the asymptotic formula remains explicit and involves a finite multiplicative factor arising from admissible sign patterns (reflecting the different ways the product can be positive); it includes an explicit first relative correction term of order $x^{-1/n}$, with remaining relative error $O(x^{-2/n})$. The proof uses a boundary saddle-point/Laplace method: first a multidimensional Laplace approximation near the boundary saddle, then a one-dimensional endpoint Laplace approximation.
title Right-tail asymptotics for products of independent normal random variables
topic Probability
url https://arxiv.org/abs/2603.08570