A chaotic decomposition for generalized stochastic processes with independent values (Q2874359)

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scientific article; zbMATH DE number 6251980
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A chaotic decomposition for generalized stochastic processes with independent values
scientific article; zbMATH DE number 6251980

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    29 January 2014
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    generalized stochastic processes
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    chaotic decomposition
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    Lévy processes
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    Fock space
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    multiple stochastic integrals
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    math.PR
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    A chaotic decomposition for generalized stochastic processes with independent values (English)
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    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.
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