Stochastic processes with jumps and random measures are importance as drivers in applications like financial mathematics and signal processing. This 2002 text develops stochastic integration theory for both integrators (semimartingales) and random measures from a common point of view. Using some novel predictable controlling devices, the author furnishes the theory of stochastic differential equations driven by them, as well as their stability and numerical approximation theories. Highlights feature DCT and Egoroff's Theorem, as well as comprehensive analogs results from ordinary integration theory, for instance previsible envelopes and an algorithm computing stochastic integrals of càglàd integrands pathwise. Full proofs are given for all results, and motivation is stressed throughout. A large appendix contains most of the analysis that readers will need as a prerequisite. This will be an invaluable reference for graduate students and researchers in mathematics, physics, electrical engineering and finance who need to use stochastic differential equations.
| ISBN: | 9780521142144 |
| Publication date: | 1st April 2010 |
| Author: | Klaus University of Texas, Austin Bichteler |
| Publisher: | Cambridge University Press |
| Format: | Paperback |
| Pagination: | 516 pages |
| Series: | Encyclopedia of Mathematics and its Applications |
| Genres: |
Differential calculus and equations Probability and statistics Stochastics |
Stochastic processes with jumps and random measures are importance as drivers in applications like financial mathematics and signal processing. This 2002 text develops stochastic integration theory for both integrators (semimartingales) and random measures from a common point of view. Using some novel predictable controlling devices, the author furnishes the theory of stochastic differential equations driven by them, as well as their stability and numerical approximation theories. Highlights feature DCT and Egoroff's Theorem, as well as comprehensive analogs results from ordinary integration theory, for instance previsible envelopes and an algorithm computing stochastic integrals of càglàd integrands pathwise. Full proofs are given for all results, and motivation is stressed throughout. A large appendix contains most of the analysis that readers will need as a prerequisite. This will be an invaluable reference for graduate students and researchers in mathematics, physics, electrical engineering and finance who need to use stochastic differential equations.
Stochastic Integration with Jumps features in the following genres: Differential calculus and equations, Probability and statistics, Stochastics
Stochastic Integration with Jumps is available in Paperback
Stochastic Integration with Jumps was written by Klaus University of Texas, Austin Bichteler and published by Cambridge University Press
Stochastic Integration with Jumps has 516 pages
Yes it is part of Encyclopedia of Mathematics and its Applications series
£72.90