Stochastic Processes
$90.99 (C)
Part of Cambridge Series in Statistical and Probabilistic Mathematics
- Author: Richard F. Bass, University of Connecticut
- Date Published: November 2011
- availability: Available
- format: Hardback
- isbn: 9781107008007
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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.
Read more- 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
Reviews & endorsements
"This is a great book which helps the graduate student to get a taste of stochastic processes and, I am sure, a good appetite, too. For instructors it is a valuable source of new topics for their next lecture course."
Rene L. Schilling, Mathematical ReviewsCustomer reviews
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×Product details
- Date Published: November 2011
- format: Hardback
- isbn: 9781107008007
- length: 408 pages
- dimensions: 254 x 183 x 25 mm
- weight: 0.91kg
- contains: 2 b/w illus. 350 exercises
- availability: Available
Table of Contents
Preface
1. Basic notions
2. Brownian motion
3. Martingales
4. Markov properties of Brownian motion
5. The Poisson process
6. Construction of Brownian motion
7. Path properties of Brownian motion
8. The continuity of paths
9. Continuous semimartingales
10. Stochastic integrals
11. Itô's formula
12. Some applications of Itô's formula
13. The Girsanov theorem
14. Local times
15. Skorokhod embedding
16. The general theory of processes
17. Processes with jumps
18. Poisson point processes
19. Framework for Markov processes
20. Markov properties
21. Applications of the Markov properties
22. Transformations of Markov processes
23. Optimal stopping
24. Stochastic differential equations
25. Weak solutions of SDEs
26. The Ray–Knight theorems
27. Brownian excursions
28. Financial mathematics
29. Filtering
30. Convergence of probability measures
31. Skorokhod representation
32. The space C[0, 1]
33. Gaussian processes
34. The space D[0, 1]
35. Applications of weak convergence
36. Semigroups
37. Infinitesimal generators
38. Dirichlet forms
39. Markov processes and SDEs
40. Solving partial differential equations
41. One-dimensional diffusions
42. Lévy processes
A. Basic probability
B. Some results from analysis
C. Regular conditional probabilities
D. Kolmogorov extension theorem
E. Choquet capacities
Frequently used notation
Index.-
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Stochastic Processes
Richard F. Bass
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