The Malliavin calculus (or stochastic calculus of variations) is an
infinite-dimensional differential calculus on a Gaussian space.
Originally, it was developed to provide a probabilistic proof to
HArmander's "sum of squares" theorem, but it has found a wide range
of applications in stochastic analysis. This monograph presents the
main features of the Malliavin calculus and discusses in detail its
main applications. The author begins by developing the analysis on
the Wiener space, and then uses this to establish the regularity of
probability laws and to prove HArmander's theorem. The regularity
of the law of stochastic partial differential equations driven by a
space-time white noise is also studied. The subsequent chapters
develop the connection of the Malliavin with the anticipating
stochastic calculus, studying anticipating stochastic differential
equations and the Markov property of solutions to stochastic
differential equations with boundary conditions.
The second edition of this monograph includes recent
applications of the Malliavin calculus in finance and a chapter
devoted to the stochastic calculus with respect to the fractional
Brownian motion.
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