Numerical Integration of Stochastic Differential Equations, Softcover reprint of hardcover 1st ed. 1995 Mathematics and Its Applications Series, Vol. 313

Mean-square approximation of solutions of systems of stochastic differential equations. Modelling of Itô integrals. Weak approximation of solutions of systems of stochastic differential equations. Applications of the numerical integration of stochastic equations for the Monte-Carlo computation of Wiener integrals.

1. Mean-square approximation of solutions of systems of stochastic differential equations.- 2. Modeling of Itô integrals.- 3. Weak approximation of solutions of systems of stochastic differential equations.- 4. Application of the numerical integration of stochastic equations for the Monte-Carlo computation of Wiener integrals.

This book is devoted to mean-square and weak approximations of solutions of stochastic differential equations (SDE). These approximations represent two fundamental aspects in the contemporary theory of SDE. Firstly, the construction of numerical methods for such systems is important as the solutions provided serve as characteristics for a number of mathematical physics problems. Secondly, the employment of probability representations together with a Monte Carlo method allows to reduce the solution of complex multidimensional problems of mathematical physics to the integration of stochastic equations.Mean-square approximation of solutions of systems of stochastic differential equations. Modelling of Itô integrals. Weak approximation of solutions of systems of stochastic differential equatio