Modeling With Ito Stochastic Differential Equations

Dynamical systems with random influences occur throughout the physical, biological, and social sciences. By carefully studying a randomly varying system over a small time interval, a discrete stochastic process model can be constructed. Next, letting the time interval shrink to zero, an Ito stochastic differential equation model for the dynamical system is obtained.

Authors: Le Gall, Jean-François
Provides a concise and rigorous presentation of stochastic integration and stochastic calculus for continuous semimartingales
Presents major applications of stochastic calculus to Brownian motion and related stochastic processes
Includes important aspects of Markov processes with applications to stochastic differential equations and to connections with partial differential equations

Introductory Stochastic Analysis for Finance and Insurance introduces readers to the topics needed to master and use basic stochastic analysis techniques for mathematical finance. The author presents the theories of stochastic processes and stochastic calculus and provides the necessary tools for modeling and pricing in finance and insurance. Practical in focus, the book's emphasis is on application, intuition, and computation, rather than theory.