Integral calculus | Calculus of variations | Mathematical finance | Stochastic calculus

Malliavin calculus

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. In particular, it allows the computation of derivatives of random variables. Malliavin calculus is also called the stochastic calculus of variations. P. Malliavin first initiated the calculus on infinite dimensional space. Then, the significant contributors such as S. Kusuoka, D. Stroock, Bismut, S. Watanabe, I. Shigekawa, and so on finally completed the foundations. Malliavin calculus is named after Paul Malliavin whose ideas led to a proof that Hörmander's condition implies the existence and smoothness of a density for the solution of a stochastic differential equation; Hörmander's original proof was based on the theory of partial differential equations. The calculus has been applied to stochastic partial differential equations as well. The calculus allows integration by parts with random variables; this operation is used in mathematical finance to compute the sensitivities of financial derivatives. The calculus has applications in, for example, stochastic filtering. (Wikipedia).

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Wiener process | Martingale representation theorem | Riesz representation theorem | Derivative | Stochastic differential equation | Probability density function | Girsanov theorem | Calculus of variations | Lebesgue integration | Malliavin derivative | Clark–Ocone theorem | Stochastic control | Predictable process | Stochastic partial differential equation | Lars Hörmander | Mathematical finance | Random variable | Skorokhod integral | Integration by parts | Hörmander's condition | Partial differential equation | Stochastic calculus