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

TL;DR

This paper analyzes the ergodic properties and law-of-large-numbers for the Volterra Cox-Ingersoll-Ross process, establishing asymptotic independence, ergodicity, and statistical estimation methods for the process.

Contribution

It provides the first detailed asymptotic analysis of the Volterra Cox-Ingersoll-Ross process, proving ergodicity, asymptotic independence, and statistical estimation consistency.

Findings

Finite-dimensional distributions are asymptotically independent.

Proves a law-of-large numbers in L^p for the process.

Establishes ergodicity of the stationary process.

Abstract

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 $L^p$(\Omega)$ 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.