Book contents
- Frontmatter
- Contents
- Preface
- Frequently used notation
- 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
- Appendices
- References
- Index
16 - The general theory of processes
Published online by Cambridge University Press: 05 June 2012
- Frontmatter
- Contents
- Preface
- Frequently used notation
- 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
- Appendices
- References
- Index
Summary
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- Stochastic Processes , pp. 111 - 129Publisher: Cambridge University PressPrint publication year: 2011