Stochastic processes
Bass, Richard F.
Stochastic processes - Cambridge: Cambridge University Press, 2013. - xv, 390p.: hbk.: 24cm. - Cambridge Series in Statistical and Probabilistic Mathematics .
Includes References and Index
This comprehensive guide to stochastic processes gives a complete overview of the theory and addresses the most important applications. Pitched at a level accessible to beginning graduate students and researchers from applied disciplines, it is both a course book and a rich resource for individual readers. Subjects covered include Brownian motion, stochastic calculus, stochastic differential equations, Markov processes, weak convergence of processes and semigroup theory. Applications include the Black–Scholes formula for the pricing of derivatives in financial mathematics, the Kalman–Bucy filter used in the US space program and also theoretical applications to partial differential equations and analysis. Short, readable chapters aim for clarity rather than full generality. More than 350 exercises are included to help readers put their new-found knowledge to the test and to prepare them for tackling the research literature.
Unlike existing books, is uniquely designed for graduate students
Fully equips students to tackle the research literature and includes 350 exercises so readers can put the theory into practice
Covers all of the necessary material for a first-year graduate course in probability
https://www.cambridge.org/in/universitypress/subjects/statistics-probability/probability-theory-and-stochastic-processes/stochastic-processes-1?format=HB
9781107008007
Stochastic Processes
Probabilistic Mathematics
Brownian Motion
Girsanov Theorem
Markov Properties
Dirichlet Forms
519.232 BAS
Stochastic processes - Cambridge: Cambridge University Press, 2013. - xv, 390p.: hbk.: 24cm. - Cambridge Series in Statistical and Probabilistic Mathematics .
Includes References and Index
This comprehensive guide to stochastic processes gives a complete overview of the theory and addresses the most important applications. Pitched at a level accessible to beginning graduate students and researchers from applied disciplines, it is both a course book and a rich resource for individual readers. Subjects covered include Brownian motion, stochastic calculus, stochastic differential equations, Markov processes, weak convergence of processes and semigroup theory. Applications include the Black–Scholes formula for the pricing of derivatives in financial mathematics, the Kalman–Bucy filter used in the US space program and also theoretical applications to partial differential equations and analysis. Short, readable chapters aim for clarity rather than full generality. More than 350 exercises are included to help readers put their new-found knowledge to the test and to prepare them for tackling the research literature.
Unlike existing books, is uniquely designed for graduate students
Fully equips students to tackle the research literature and includes 350 exercises so readers can put the theory into practice
Covers all of the necessary material for a first-year graduate course in probability
https://www.cambridge.org/in/universitypress/subjects/statistics-probability/probability-theory-and-stochastic-processes/stochastic-processes-1?format=HB
9781107008007
Stochastic Processes
Probabilistic Mathematics
Brownian Motion
Girsanov Theorem
Markov Properties
Dirichlet Forms
519.232 BAS
