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El. knyga: Stochastic Integration by Parts and Functional Ito Calculus

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This volume contains lecture notes from the courses given by Vlad Bally and Rama Cont at the Barcelona Summer School on Stochastic Analysis (July 2012).

The notes of the course by Vlad Bally, co-authored with Lucia Caramellino, develop integration by parts formulas in an abstract setting, extending Malliavin's work on abstract Wiener spaces. The results are applied to prove absolute continuity and regularity results of the density for a broad class of random processes.

Rama Cont's notes provide an introduction to the Functional Itō Calculus, a non-anticipative functional calculus that extends the classical Itō calculus to path-dependent functionals of stochastic processes. This calculus leads to a new class of path-dependent partial differential equations, termed Functional Kolmogorov Equations, which arise in the study of martingales and forward-backward stochastic differential equations.This book will appeal to both young and senior researchers in probability and stochastic processes, as well as to practitioners in mathematical finance.
I Integration by Parts Formulas, Malliavin Calculus, and Regularity of Probability Laws
1(114)
Vlad Bally
Ucia Caramellino
Preface
3(6)
1 Integration by parts formulas and the Riesz transform
9(24)
1.1 Sobolev spaces associated to probability measures
11(2)
1.2 The Riesz transform
13(2)
1.3 Malliavin--Thalmaier representation formula
15(2)
1.4 Estimate of the Riesz transform
17(4)
1.5 Regularity of the density
21(2)
1.6 Estimate of the tails of the density
23(2)
1.7 Local integration by parts formulas and local densities
25(2)
1.8 Random variables
27(6)
2 Construction of integration by parts formulas
33(50)
2.1 Construction of integration by parts formulas
34(16)
2.1.1 Derivative operators
34(2)
2.1.2 Duality and integration by parts formulas
36(2)
2.1.3 Estimation of the weights
38(9)
2.1.4 Norms and weights
47(3)
2.2 Short introduction to Malliavin calculus
50(12)
2.2.1 Differential operators
50(7)
2.2.2 Computation rules and integration by parts formulas
57(5)
2.3 Representation and estimates for the density
62(2)
2.4 Comparisons between density functions
64(9)
2.4.1 Localized representation formulas for the density
64(4)
2.4.2 The distance between density functions
68(5)
2.5 Convergence in total variation for a sequence of Wiener functionals
73(10)
3 Regularity of probability laws by using an interpolation method
83(32)
3.1 Notations
83(1)
3.2 Criterion for the regularity of a probability law
84(7)
3.3 Random variables and integration by parts
91(3)
3.4 Examples
94(6)
3.4.1 Path dependent SDE's
94(1)
3.4.2 Diffusion processes
95(2)
3.4.3 Stochastic heat equation
97(3)
3.5 Appendix A: Hermite expansions and density estimates
100(6)
3.6 Appendix B: Interpolation spaces
106(2)
3.7 Appendix C: Superkernels
108(7)
Bibliography
111(4)
II Functional Ito Calculus and Functional Kolmogorov Equations
115
Rama Cont
Preface
117(2)
4 Overview
119(6)
4.1 Functional Ito Calculus
119(1)
4.2 Martingale representation formulas
120(1)
4.3 Functional Kolmogorov equations and path dependent PDEs
121(1)
4.4 Outline
121(4)
5 Pathwise calculus for non-anticipative functionals
125(28)
5.1 Non-anticipative functionals
126(2)
5.2 Horizontal and vertical derivatives
128(7)
5.2.1 Horizontal derivative
129(1)
5.2.2 Vertical derivative
130(1)
5.2.3 Regular functionals
131(4)
5.3 Pathwise integration and functional change of variable formula
135(10)
5.3.1 Pathwise quadratic variation
135(4)
5.3.2 Functional change of variable formula
139(3)
5.3.3 Pathwise integration for paths of finite quadratic variation
142(3)
5.4 Functionals defined on continuous paths
145(6)
5.5 Application to functionals of stochastic processes
151(2)
6 The functional Ito formula
153(10)
6.1 Semimartingales and quadratic variation
153(2)
6.2 The functional Ito formula
155(3)
6.3 Functionals with dependence on quadratic variation
158(5)
7 Weak functional calculus for square-integrable processes
163(20)
7.1 Vertical derivative of an adapted process
164(3)
7.2 Martingale representation formula
167(2)
7.3 Weak derivative for square integrable functionals
169(3)
7.4 Relation with the Malliavin derivative
172(3)
7.5 Extension to semimartingales
175(4)
7.6 Changing the reference martingale
179(1)
7.7 Forward-Backward SDEs
180(3)
8 Functional Kolmogorov equations (with D. Fournie)
183
8.1 Functional Kolmogorov equations and harmonic functionals
184(7)
8.1.1 SDEs with path dependent coefficients
184(2)
8.1.2 Local martingales and harmonic functionals
186(2)
8.1.3 Sub-solutions and super-solutions
188(1)
8.1.4 Comparison principle and uniqueness
189(1)
8.1.5 Feynman--Kac formula for path dependent functionals
190(1)
8.2 FBSDEs and semilinear functional PDEs
191(2)
8.3 Non-Markovian control and path dependent HJB equations
193(3)
8.4 Weak solutions
196
Bibliography
203