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Theory of Stochastic Integrals / Jorge A. León.

By:

León, Jorge A [author.]

Material type:

TextPublisher: Boca Raton : CRC Press, Taylor & Francis Group, 2025Edition: First editionDescription: 1 online resource (xiv, 472 pages)Content type:

text

Media type:

computer

Carrier type:

online resource

ISBN:

9781003484912
1003484913
9781040322970
1040322972
9781040323014
1040323014

Subject(s):

LOC classification:

QA274.22

Online resources:

Contents:

1. Basic Tool and Concepts. 2. Riemann-Stieltjes integral. 3. Classical Stochastic Integration. 4. Divergence Operator. 5. Forward Integration. 6. Stratonovich Integration. 7. Stochastic Differential Equations. 8. Appendix.

Summary: 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 topic Suitable as a teaching or research tool for those interested in stochastic analysis and its applications Includes original results.

Item type: List(s) this item appears in: Titluri cărți electronice Taylor&Francis 2025 (1039 titluri)

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“A Chapman & Hall Book.”

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 topic Suitable as a teaching or research tool for those interested in stochastic analysis and its applications Includes original results.

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