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Gaussian Moving Averages and Semimartingales

Dublin Core		PKP Metadata Items	Metadata for this Document
1.	Title	Title of document	Gaussian Moving Averages and Semimartingales
2.	Creator	Author's name, affiliation, country	Andreas Basse; Department of Mathematical Sciences, University of Aarhus
3.	Subject	Discipline(s)
3.	Subject	Keyword(s)	semimartingales; Gaussian processes; stationary processes; moving averages; stochastic convolutions; non-canonical representations
3.	Subject	Subject classification	60G15; 60G10; 60G48; 60G57
4.	Description	Abstract	In the present paper we study moving averages (also known as stochastic convolutions) driven by a Wiener process and with a deterministic kernel. Necessary and sufficient conditions on the kernel are provided for the moving average to be a semimartingale in its natural filtration. Our results are constructive - meaning that they provide a simple method to obtain kernels for which the moving average is a semimartingale or a Wiener process. Several examples are considered. In the last part of the paper we study general Gaussian processes with stationary increments. We provide necessary and sufficient conditions on spectral measure for the process to be a semimartingale.
5.	Publisher	Organizing agency, location
6.	Contributor	Sponsor(s)
7.	Date	(YYYY-MM-DD)	2008-07-22
8.	Type	Status & genre	Peer-reviewed Article
8.	Type	Type
9.	Format	File format	PDF
10.	Identifier	Uniform Resource Identifier	http://ejp.ejpecp.org/article/view/526
10.	Identifier	Digital Object Identifier	10.1214/EJP.v13-526
11.	Source	Journal/conference title; vol., no. (year)	Electronic Journal of Probability; Vol 13
12.	Language	English=en
14.	Coverage	Geo-spatial location, chronological period, research sample (gender, age, etc.)
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