Ergodicity and Law-of-large numbers for the Volterra Cox-Ingersoll-Ross process

Fuente: arXiv
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Main Authors: Alaya, Mohamed Ben, Friesen, Martin, Kremer, Jonas
Format: Preprint
Published: 2024
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author Alaya, Mohamed Ben
Friesen, Martin
Kremer, Jonas
author_facet Alaya, Mohamed Ben
Friesen, Martin
Kremer, Jonas
contents We study the Volterra Volterra Cox-Ingersoll-Ross process on $\mathbb{R}_+$ and its stationary version. Based on a fine asymptotic analysis of the corresponding Volterra Riccati equation combined with the affine transformation formula, we first show that the finite-dimensional distributions of this process are asymptotically independent. Afterwards, we prove a law-of-large numbers in $L^p$(Ω)$ with $p \geq 2$ and show that the stationary process is ergodic. As an application, we prove the consistency of the method of moments and study the maximum-likelihood estimation for continuous and discrete high-frequency observations.
format Preprint
id arxiv_https___arxiv_org_abs_2409_04496
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Ergodicity and Law-of-large numbers for the Volterra Cox-Ingersoll-Ross process
Alaya, Mohamed Ben
Friesen, Martin
Kremer, Jonas
Probability
Mathematical Finance
We study the Volterra Volterra Cox-Ingersoll-Ross process on $\mathbb{R}_+$ and its stationary version. Based on a fine asymptotic analysis of the corresponding Volterra Riccati equation combined with the affine transformation formula, we first show that the finite-dimensional distributions of this process are asymptotically independent. Afterwards, we prove a law-of-large numbers in $L^p$(Ω)$ with $p \geq 2$ and show that the stationary process is ergodic. As an application, we prove the consistency of the method of moments and study the maximum-likelihood estimation for continuous and discrete high-frequency observations.
title Ergodicity and Law-of-large numbers for the Volterra Cox-Ingersoll-Ross process
topic Probability
Mathematical Finance
url https://arxiv.org/abs/2409.04496