Martingale transforms and Girsanov theorem for long-memory Gaussian processes
type: Item
instance of: scholarly article
title: Martingale transforms and Girsanov theorem for long-memory Gaussian processes
zbMATH Open document ID: 1002.60030
DOI: 10.1016/S0167-7152(01)00162-6
author: Esko Valkeila
author: Yuliya S. Mishura
published in: Statistics \& Probability Letters
publication date: 2002-09-05T00:00:00Z
review text: Long-memory Gaussian processes presented as stochastic integrals with respect to a standard Wiener process are considered. The fractional Brownian motion is a particular case when the integrands are the power functions. The integrals are transformed into Gaussian martingales. The Girsanov theorem for the long-memory Gaussian processes is stated and the Hellinger process is calculated.
reviewed by: Yuhu Feng
Mathematics Subject Classification ID: 60G15
Mathematics Subject Classification ID: 60G44
Mathematics Subject Classification ID: 60H05
zbMATH DE Number: 1796648
zbMATH Keywords: long-memory Gaussian processes
zbMATH Keywords: martingale transforms
zbMATH Keywords: Girsanov theorem
zbMATH Keywords: Hellinger process
describes a project that uses: longmemo
MaRDI profile type: Publication
cites work: Q4865042
cites work: Approximation of some processes
cites work: Stochastic analysis of the fractional Brownian motion
cites work: Stochastic and multiple Wiener integrals for Gaussian processes
cites work: Q4856610
cites work: An elementary approach to filtering in systems with fractional Brownian observation noise
cites work: Q4866403
cites work: An elementary approach to a Girsanov formula and other analytical results on fractional Brownian motions
cites work: Stochastic differential equations. An introduction with applications.
cites work: Stock market prices and long-range dependence
Wikidata QID: Q127863456
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description: scientific article; zbMATH DE number 1796648