Numerical Solution of Stochastic Differential Equations (Applications of Mathematics)

Peter E. Kloeden; Eckhard Platen; A.V. Balakrishnan; I. Karatzas; Marc Yor

ISBN 10: 0387540628 / ISBN 13: 9780387540627

Published by Springer Verlag, 1992

About this Item

Book is in very nice condition, text is unmarked and pages are tight.

Seller Inventory # 68356

Bibliographic Details

• Title: Numerical Solution of Stochastic Differential Equations (Applications of Mathematics)
• Publisher: Springer Verlag
• Publication Date: 1992
• Language: English
• ISBN 10: 0387540628
• ISBN 13: 9780387540627
• Binding: hardcover
• Condition: Very Good
• Weight: 8 ounces

About this title

Synopsis

The numerical analysis of stochastic differential equations differs significantly from that of ordinary differential equations, due to the peculiarities of stochastic calculus. The book proposes to the reader whose background knowledge is limited to undergraduate level methods for engineering and physics, and easily accessible introductions to SDE and then applications as well as the numerical methods for dealing with them. To help the reader develop an intuitive understanding and hand-on numerical skills, numerous exercises including PC-exercises are included.

From the Back Cover

The numerical analysis of stochastic differential equations differs significantly from that of ordinary differential equations due to peculiarities of stochastic calculus. This book provides an introduction to stochastic calculus and stochastic differential equations, in both theory and applications, emphasising the numerical methods needed to solve such equations. It assumes of the reader an undergraduate background in mathematical methods typical of engineers and physicists, though many chapters begin with a descriptive summary. The book is also accessible to others who only require numerical recipes. The stochastic Taylor expansion provides the basis for the discrete time numerical methods for differential equations. The book presents many new results on high-order methods for strong sample path approximations and for weak functional approximations, including implicit, predictor-corrector, extra-polation and variance-reduction methods. Besides serving as a basic text on such methods, the book offers the reader ready access to a large number of potential research problems in a field that is just beginning to expand rapidly and is widely applicable. To help the reader to develop an intuitive understanding of the underlying mathematics and hand-on numerical skills, exercises and over 100 PC-Exercises are included.