Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
10527275 | Stochastic Processes and their Applications | 2012 | 32 Pages |
Abstract
De Haan and Karandikar (1989) [7] introduced generalized Ornstein-Uhlenbeck processes as one-dimensional processes (Vt)tâ¥0 which are basically characterized by the fact that for each h>0 the equidistantly sampled process (Vnh)nâN0 satisfies the random recurrence equation Vnh=A(nâ1)h,nhV(nâ1)h+B(nâ1)h,nh, nâN, where (A(nâ1)h,nh,B(nâ1)h,nh)nâN is an i.i.d. sequence with positive A0,h for each h>0. We generalize this concept to a multivariate setting and use it to define multivariate generalized Ornstein-Uhlenbeck (MGOU) processes which occur to be characterized by a starting random variable and some Lévy process (X,Y) in RmÃmÃRm. The stochastic differential equation an MGOU process satisfies is also derived. We further study invariant subspaces and irreducibility of the models generated by MGOU processes and use this to give necessary and sufficient conditions for the existence of strictly stationary MGOU processes under some extra conditions.
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Physical Sciences and Engineering
Mathematics
Mathematics (General)
Authors
Anita Behme, Alexander Lindner,