Lévy Area Analysis and Parameter Estimation for fOU Processes via Non-Geometric Rough Path Theory

Fuente: arXiv
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Autores principales: Qian, Zhongmin, Xu, Xingcheng
Formato: Preprint
Publicado: 2018
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author Qian, Zhongmin
Xu, Xingcheng
author_facet Qian, Zhongmin
Xu, Xingcheng
contents This paper addresses the estimation problem of an unknown drift parameter matrix for a fractional Ornstein-Uhlenbeck process in a multi-dimensional setting. To tackle this problem, we propose a novel approach based on rough path theory that allows us to construct pathwise rough path estimators from both continuous and discrete observations of a single path. Our approach is particularly suitable for high-frequency data. To formulate the parameter estimators, we introduce a theory of pathwise Itô integrals with respect to fractional Brownian motion. By establishing the regularity of fractional Ornstein-Uhlenbeck processes and analyzing the long-term behavior of the associated Lévy area processes, we demonstrate that our estimators are strongly consistent and pathwise stable. Our findings offer a new perspective on estimating the drift parameter matrix for fractional Ornstein-Uhlenbeck processes in multi-dimensional settings, and may have practical implications for fields including finance, economics, and engineering.
format Preprint
id arxiv_https___arxiv_org_abs_1803_11039
institution arXiv
publishDate 2018
record_format arxiv
spellingShingle Lévy Area Analysis and Parameter Estimation for fOU Processes via Non-Geometric Rough Path Theory
Qian, Zhongmin
Xu, Xingcheng
Probability
Statistics Theory
60H05, 62F12, 62M09, 91G30
This paper addresses the estimation problem of an unknown drift parameter matrix for a fractional Ornstein-Uhlenbeck process in a multi-dimensional setting. To tackle this problem, we propose a novel approach based on rough path theory that allows us to construct pathwise rough path estimators from both continuous and discrete observations of a single path. Our approach is particularly suitable for high-frequency data. To formulate the parameter estimators, we introduce a theory of pathwise Itô integrals with respect to fractional Brownian motion. By establishing the regularity of fractional Ornstein-Uhlenbeck processes and analyzing the long-term behavior of the associated Lévy area processes, we demonstrate that our estimators are strongly consistent and pathwise stable. Our findings offer a new perspective on estimating the drift parameter matrix for fractional Ornstein-Uhlenbeck processes in multi-dimensional settings, and may have practical implications for fields including finance, economics, and engineering.
title Lévy Area Analysis and Parameter Estimation for fOU Processes via Non-Geometric Rough Path Theory
topic Probability
Statistics Theory
60H05, 62F12, 62M09, 91G30
url https://arxiv.org/abs/1803.11039