We give a short introduction to Malliavin calculus which finishes with the proof The Malliavin derivative and the Skorohod integral in the finite. Application du calcul de Malliavin aux problèmes de contrôle singulier. Devant le jury. Abdelhakim Necir. Pr. UMK Biskra Président. Brahim Mezerdi. Pr. Using multiple Wiener%It/o stochastic integrals and Malliavin calculus we servant des int egrales multiples de Wiener%It/o et du calcul de Malliavin, nous.

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Malliavin calculus

Stochastic calculus Integral calculus Mathematical finance Calculus of variations. The calculus has been applied to stochastic partial differential equations as well.

This page was last edited on 12 Octoberat One of the most useful results from Malliavin calculus is mmalliavin Clark-Ocone theoremwhich allows the process in the martingale representation theorem to be identified explicitly. Malliavin calculus is also called the stochastic calculus of variations.


Application du calcul de Malliavin aux équations différentielles stochastiques sur le plan

All articles with unsourced statements Articles with unsourced statements from August Articles lacking in-text citations from June All articles lacking in-text citations. The existence of this adjoint follows from the Riesz representation theorem for linear operators on Hilbert spaces.

June Learn how and when to remove this template message. Falcul Read Edit View history. In probability theory and related fields, Malliavin calculus is a set of mathematical techniques and ideas that extend the mathematical field of calculus of variations from deterministic functions to stochastic processes.

His calculus enabled Malliavin to prove regularity bounds for the solution’s density. The calculus has applications in, for example, stochastic filtering. By using this site, you agree to the Terms of Use and Privacy Policy.

A simplified version of this theorem is as follows:. The calculus has been applied to stochastic partial differential equations.

Retrieved from ” https: From Wikipedia, the free encyclopedia. The calculus has applications for example in stochastic filtering.


A similar idea can be applied in stochastic analysis for the differentiation along a Cameron-Martin-Girsanov direction. The calculus allows integration by parts with random variables ; this operation is used in mathematical malilavin to compute the sensitivities of financial derivatives.

This article includes a list of claculrelated reading or external linksbut its sources remain unclear because it lacks inline citations. Please help to improve this article by introducing more precise citations. In particular, it allows the computation of derivatives of random variables.