Stochastic Calculus of Variations in Mathematical Finance (Springer Finance)

Malliavin calculus provides an infinite-dimensional differential calculus in the context of continuous paths stochastic processes. The calculus includes formulae of integration by parts and Sobolev spaces of differentiable functions defined on a probability space. This new book, demonstrating the relevance of Malliavin calculus for Mathematical Finance, starts with an exposition from scratch of this theory. Greeks (price sensitivities) are reinterpreted in terms of Malliavin calculus. Integration by parts formulae provide stable Monte Carlo schemes for numerical valuation of digital options. Finite-dimensional projections of infinite-dimensional Sobolev spaces lead to Monte Carlo computations of conditional expectations useful for computing American options. The discretization error of the Euler scheme for a stochastic differential equation is expressed as a generalized Watanabe distribution on the Wiener space. Insider information is expressed as an infinite-dimensional drift. The last chapter gives an introduction to the same objects in the context of jump processes where incomplete markets appear. Malliavin calculus provides an infinite-dimensional differential calculus in the context of continuous paths stochastic processes. The calculus includes formulae of integration by parts and Sobolev spaces of differentiable functions defined on a probability space. This new book, demonstrating the relevance of Malliavin calculus for Mathematical Finance, starts with an exposition from scratch of this theory. Greeks (price sensitivities) are reinterpreted in terms of Malliavin calculus. Integration by parts formulae provide stable Monte Carlo schemes for numerical valuation of digital options. Finite-dimensional projections of infinite-dimensional Sobolev spaces lead to Monte Carlo computations of conditional expectations useful for computing American options. Weak convergence of numerical integration of SDE is interpreted as a functional belonging to a Sobolev space of negative order. Insider information is expressed as an infinite-dimensional drift. The last chapter gives an introduction to the same objects in the context of jump processes where incomplete markets appear. Gaussian Stochastic Calculus of Variations....Pages 1-23 Computation of Greeks and Integration by Parts Formulae....Pages 25-40 Market Equilibrium and Price-Volatility Feedback Rate....Pages 41-48 Multivariate Conditioning and Regularity of Law....Pages 49-63 Non-Elliptic Markets and Instability in HJM Models....Pages 65-76 Insider Trading....Pages 77-85 Asymptotic Expansion and Weak Convergence....Pages 87-96 Stochastic Calculus of Variations for Markets with Jumps....Pages 97-105 Highly esteemed author Topics covered are relevant and timely