Diffusions, Markov Processes and Martingales Ito Calculus

Klappentext Now available in paperback for the first time; essential reading for all students of probability theory. Zusammenfassung This celebrated volume gives an accessible introduction to stochastic integrals! stochastic differential equations! excursion theory and the general theory of processes. Together with its companion! it helps equip graduate students for research into a subject of great intrinsic interest and wide application. Inhaltsverzeichnis Some frequently used notation; 4. Introduction to Ito calculus; 4.1. Some motivating remarks; 4.2. Some fundamental ideas: previsible processes, localization, etc.; 4.3. The elementary theory of finite-variation processes; 4.4. Stochastic integrals: the L2 theory; 4.5. Stochastic integrals with respect to continuous semimartingales; 4.6. Applications of Ito's formula; 5. Stochastic differential equations and diffusions; 5.1. Introduction; 5.2. Pathwise uniqueness, strong SDEs, flows; 5.3. Weak solutions, uniqueness in law; 5.4. Martingale problems, Markov property; 5.5. Overture to stochastic differential geometry; 5.6. One-dimensional SDEs; 5.7. One-dimensional diffusions; 6. The general theory; 6.1. Orientation; 6.2. Debut and section theorems; 6.3. Optional projections and filtering; 6.4. Characterising previsible times; 6.5. Dual previsible projections; 6.6. The Meyer decomposition theorem; 6.7. Stochastic integration: the general case; 6.8. Ito excursion theory; References; Index.

Produktdetails

• Autoren: L. C. G. Rogers, L.c.g. Williams Rogers, Rogers L. C. G., D. Williams, David Williams
• Verlag: Cambridge University Press Academic
• Sprache: Englisch
• Produktform: Taschenbuch
• Erschienen: 07.09.2000
• EAN: 9780521775939
• ISBN: 978-0-521-77593-9
• Abmessung: 153 mm x 228 mm x 23 mm
• Serien: Cambridge Mathematical Library; Diffusions, Markov Processes &; Cambridge Mathematical Library
• Themen: Naturwissenschaften, Medizin, Informatik, Technik > Mathematik; MATHEMATICS / Number Theory, Number Theory, Stochastics