The Ornstein-Uhlenbeck bridge and applications to Markov semigroups
B. Goldys and
B. Maslowski
Stochastic Processes and their Applications, 2008, vol. 118, issue 10, 1738-1767
Abstract:
For an arbitrary Hilbert space-valued Ornstein-Uhlenbeck process we construct the Ornstein-Uhlenbeck bridge connecting a given starting point x and an endpoint y provided y belongs to a certain linear subspace of full measure. We derive also a stochastic evolution equation satisfied by the OU bridge and study its basic properties. The OU bridge is then used to investigate the Markov transition semigroup defined by a stochastic evolution equation with additive noise. We provide an explicit formula for the transition density and study its regularity. These results are applied to show some basic properties of the transition semigroup. Given the strong Feller property and the existence of invariant measure we show that all Lp functions are transformed into continuous functions, thus generalising the strong Feller property. We also show that transition operators are q-summing for some q>p>1, in particular of Hilbert-Schmidt type.
Keywords: Ornstein-Uhlenbeck; process; Pinned; process; Measurable; linear; mapping; Stochastic; semilinear; equation; Transition; density (search for similar items in EconPapers)
Date: 2008
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)
Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0304-4149(07)00182-2
Full text for ScienceDirect subscribers only
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:eee:spapps:v:118:y:2008:i:10:p:1738-1767
Ordering information: This journal article can be ordered from
http://http://www.elsevier.com/wps/find/supportfaq.cws_home/regional
https://shop.elsevie ... _01_ooc_1&version=01
Access Statistics for this article
Stochastic Processes and their Applications is currently edited by T. Mikosch
More articles in Stochastic Processes and their Applications from Elsevier
Bibliographic data for series maintained by Catherine Liu ().