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Main Authors: Bayraktar, Elise, Clément, Emmanuelle
Format: Preprint
Published: 2024
Subjects:
Online Access:https://arxiv.org/abs/2407.21411
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author Bayraktar, Elise
Clément, Emmanuelle
author_facet Bayraktar, Elise
Clément, Emmanuelle
contents We consider the parametric estimation of the volatility and jump activity in a stable Cox-Ingersoll-Ross ($α$-stable CIR) model driven by a standard Brownian Motion and a non-symmetric stable Lévy process with jump activity $α\in (1,2)$. The main difficulties to obtain rate efficiency in estimating these quantities arise from the superposition of the diffusion component with jumps of infinite variation. Extending the approach proposed in Mies (2020), we address the joint estimation of the volatility, scaling and jump activity parameters from high-frequency observations of the process and prove that the proposed estimators are rate optimal up to a logarithmic factor.
format Preprint
id arxiv_https___arxiv_org_abs_2407_21411
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Volatility and jump activity estimation in a stable Cox-Ingersoll-Ross model
Bayraktar, Elise
Clément, Emmanuelle
Statistics Theory
We consider the parametric estimation of the volatility and jump activity in a stable Cox-Ingersoll-Ross ($α$-stable CIR) model driven by a standard Brownian Motion and a non-symmetric stable Lévy process with jump activity $α\in (1,2)$. The main difficulties to obtain rate efficiency in estimating these quantities arise from the superposition of the diffusion component with jumps of infinite variation. Extending the approach proposed in Mies (2020), we address the joint estimation of the volatility, scaling and jump activity parameters from high-frequency observations of the process and prove that the proposed estimators are rate optimal up to a logarithmic factor.
title Volatility and jump activity estimation in a stable Cox-Ingersoll-Ross model
topic Statistics Theory
url https://arxiv.org/abs/2407.21411