In applications of stochastic calculus, there are phenomena that cannot be analyzed through the classical Itô theory. It is necessary, therefore, to have a theory based on stochastic integration with respect to these situations.
Theory of Stochastic Integrals aims to provide the answer to this problem by introducing readers to the study of some interpretations of stochastic integrals with respect to stochastic processes that are not necessarily semimartingales, such as Volterra Gaussian processes, or processes with bounded p-variation among which we can mention fractional Brownian motion and Riemann-Liouville fractional process.
Features
Self-contained treatment of the topicSuitable as a teaching or research tool for those interested in stochastic analysis and its applicationsIncludes original results.
Theory of Stochastic Integrals aims to provide the answer to this problem by introducing readers to the study of some interpretations of stochastic integrals with respect to stochastic processes that are not necessarily semimartingales, such as Volterra Gaussian processes, or processes with bounded p-variation among which we can mention fractional Brownian motion and Riemann-Liouville fractional process.
Features
Self-contained treatment of the topicSuitable as a teaching or research tool for those interested in stochastic analysis and its applicationsIncludes original results.
"A fundamental, comprehensive, and detailed introduction to stochastic integrals, Theory of Stochastic Integrals is an ideal and unreservedly recommended pick for professional and college/university library collections and as a supplemental Calculus curriculum textbook."
--Midwest Book Review
--Midwest Book Review







