A chaotic decomposition for generalized stochastic processes with independent values (Q2874359)
From MaRDI portal
| This is the item page for this Wikibase entity, intended for internal use and editing purposes. Please use this page instead for the normal view: A chaotic decomposition for generalized stochastic processes with independent values |
scientific article; zbMATH DE number 6251980
| Language | Label | Description | Also known as |
|---|---|---|---|
| English | A chaotic decomposition for generalized stochastic processes with independent values |
scientific article; zbMATH DE number 6251980 |
Statements
29 January 2014
0 references
generalized stochastic processes
0 references
chaotic decomposition
0 references
Lévy processes
0 references
Fock space
0 references
multiple stochastic integrals
0 references
math.PR
0 references
0.6970496
0 references
0 references
0.67017007
0 references
0 references
0.6690056
0 references
0.6684324
0 references
A chaotic decomposition for generalized stochastic processes with independent values (English)
0 references
The article aims to extend the Nualart-Schoutens decomposition for Lévy processes to what the authors call generalized stochastic processes with independent values. \textit{D. Nualart} and \textit{W. Schoutens} [Stochastic Processes Appl. 90, No. 1, 109--122 (2000; Zbl 1047.60088)] constructed a representation for square-integrable functionals of a Lévy process in terms of the orthogonalized Teugels martingales. For a certain class of generalized stochastic processes with independent values, the authors construct an orthogonal decomposition of the space \(L^{2}\left( \mathcal{D}^{\prime}, d\mu \right)\), which in the case of a Lévy process is the Nualart-Schoutens decomposition. Here, \(\mathcal{D}^{\prime}\) is the dual of the nuclear space \(\mathcal{D}=C_{0}^{\infty}\left( \mathbb{R}^{d}\right)\).NEWLINENEWLINEFirst, the authors consider an orthogonal decomposition of a particular symmetric Fock space, \(\mathcal{F}\left( H \right)\), where \(H=L^{2}\left( \mathbb{R}^{d} \times \mathbb{R}, dx \sigma(x,ds) \right)\). Then, they use the fact that the set of polynomials is dense in \(L^{2}\left( \mathbb{R},\sigma(x,ds) \right)\), and under a certain condition on monic polynomials which are orthogonal with respect to the measure \(\sigma(x,ds)\), one can find an orthogonal decomposition of \(L^{2}\left( \mathcal{D}^{\prime}, d\mu \right)\). Finally, this decomposition is described in terms of multiple stochastic integrals.
0 references