Introduction to Stochastic Analysis and Malliavin Calculus
Introduction to Stochastic Analysis and Malliavin Calculus

Author: Giuseppe Da Prato

Publisher: Springer

Published: 2014-07-01

Total Pages: 286

ISBN-13: 8876424997

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This volume presents an introductory course on differential stochastic equations and Malliavin calculus. The material of the book has grown out of a series of courses delivered at the Scuola Normale Superiore di Pisa (and also at the Trento and Funchal Universities) and has been refined over several years of teaching experience in the subject. The lectures are addressed to a reader who is familiar with basic notions of measure theory and functional analysis. The first part is devoted to the Gaussian measure in a separable Hilbert space, the Malliavin derivative, the construction of the Brownian motion and Itô's formula. The second part deals with differential stochastic equations and their connection with parabolic problems. The third part provides an introduction to the Malliavin calculus. Several applications are given, notably the Feynman-Kac, Girsanov and Clark-Ocone formulae, the Krylov-Bogoliubov and Von Neumann theorems. In this third edition several small improvements are added and a new section devoted to the differentiability of the Feynman-Kac semigroup is introduced. A considerable number of corrections and improvements have been made.

Stochastic Analysis for Poisson Point Processes
Stochastic Analysis for Poisson Point Processes

Author: Giovanni Peccati

Publisher: Springer

Published: 2016-07-07

Total Pages: 359

ISBN-13: 3319052330

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Stochastic geometry is the branch of mathematics that studies geometric structures associated with random configurations, such as random graphs, tilings and mosaics. Due to its close ties with stereology and spatial statistics, the results in this area are relevant for a large number of important applications, e.g. to the mathematical modeling and statistical analysis of telecommunication networks, geostatistics and image analysis. In recent years – due mainly to the impetus of the authors and their collaborators – a powerful connection has been established between stochastic geometry and the Malliavin calculus of variations, which is a collection of probabilistic techniques based on the properties of infinite-dimensional differential operators. This has led in particular to the discovery of a large number of new quantitative limit theorems for high-dimensional geometric objects. This unique book presents an organic collection of authoritative surveys written by the principal actors in this rapidly evolving field, offering a rigorous yet lively presentation of its many facets.

Malliavin Calculus for Lévy Processes with Applications to Finance
Malliavin Calculus for Lévy Processes with Applications to Finance

Author: Giulia Di Nunno

Publisher: Springer Science & Business Media

Published: 2008-10-08

Total Pages: 421

ISBN-13: 3540785728

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This book is an introduction to Malliavin calculus as a generalization of the classical non-anticipating Ito calculus to an anticipating setting. It presents the development of the theory and its use in new fields of application.

Stochastic Analysis
Stochastic Analysis

Author: Hiroyuki Matsumoto

Publisher: Cambridge University Press

Published: 2017

Total Pages: 359

ISBN-13: 110714051X

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Developing the Itô calculus and Malliavin calculus in tandem, this book crystallizes modern day stochastic analysis into a single volume.

Malliavin Calculus and Stochastic Analysis
Malliavin Calculus and Stochastic Analysis

Author: Frederi Viens

Publisher: Springer Science & Business Media

Published: 2013-02-15

Total Pages: 580

ISBN-13: 1461459060

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The stochastic calculus of variations of Paul Malliavin (1925 - 2010), known today as the Malliavin Calculus, has found many applications, within and beyond the core mathematical discipline. Stochastic analysis provides a fruitful interpretation of this calculus, particularly as described by David Nualart and the scores of mathematicians he influences and with whom he collaborates. Many of these, including leading stochastic analysts and junior researchers, presented their cutting-edge research at an international conference in honor of David Nualart's career, on March 19-21, 2011, at the University of Kansas, USA. These scholars and other top-level mathematicians have kindly contributed research articles for this refereed volume.

Introduction to Malliavin Calculus
Introduction to Malliavin Calculus

Author: David Nualart

Publisher: Cambridge University Press

Published: 2018-09-27

Total Pages: 249

ISBN-13: 1107039126

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A compact introduction to this active and powerful area of research, combining basic theory, core techniques, and recent applications.

The Malliavin Calculus and Related Topics
The Malliavin Calculus and Related Topics

Author: David Nualart

Publisher: Springer Science & Business Media

Published: 2013-12-11

Total Pages: 273

ISBN-13: 1475724373

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The origin of this book lies in an invitation to give a series of lectures on Malliavin calculus at the Probability Seminar of Venezuela, in April 1985. The contents of these lectures were published in Spanish in [176]. Later these notes were completed and improved in two courses on Malliavin cal culus given at the University of California at Irvine in 1986 and at Ecole Polytechnique Federale de Lausanne in 1989. The contents of these courses correspond to the material presented in Chapters 1 and 2 of this book. Chapter 3 deals with the anticipating stochastic calculus and it was de veloped from our collaboration with Moshe Zakai and Etienne Pardoux. The series of lectures given at the Eighth Chilean Winter School in Prob ability and Statistics, at Santiago de Chile, in July 1989, allowed us to write a pedagogical approach to the anticipating calculus which is the basis of Chapter 3. Chapter 4 deals with the nonlinear transformations of the Wiener measure and their applications to the study of the Markov property for solutions to stochastic differential equations with boundary conditions.

Stochastic Analysis
Stochastic Analysis

Author: Ichirō Shigekawa

Publisher: American Mathematical Soc.

Published: 2004

Total Pages: 202

ISBN-13: 9780821826263

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This book offers a concise introduction to stochastic analysis, particularly the Malliavin calculus. A detailed description is given of all technical tools necessary to describe the theory, such as the Wiener process, the Ornstein-Uhlenbeck process, and Sobolev spaces. Applications of stochastic cal

Interest Rate Models: an Infinite Dimensional Stochastic Analysis Perspective
Interest Rate Models: an Infinite Dimensional Stochastic Analysis Perspective

Author: René Carmona

Publisher: Springer Science & Business Media

Published: 2007-05-22

Total Pages: 236

ISBN-13: 3540270671

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This book presents the mathematical issues that arise in modeling the interest rate term structure by casting the interest-rate models as stochastic evolution equations in infinite dimensions. The text includes a crash course on interest rates, a self-contained introduction to infinite dimensional stochastic analysis, and recent results in interest rate theory. From the reviews: "A wonderful book. The authors present some cutting-edge math." --WWW.RISKBOOK.COM

An Introduction to Analysis on Wiener Space
An Introduction to Analysis on Wiener Space

Author: Ali S. Üstünel

Publisher: Springer

Published: 2006-11-14

Total Pages: 103

ISBN-13: 3540446621

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This book gives the basis of the probabilistic functional analysis on Wiener space, developed during the last decade. The subject has progressed considerably in recent years thr- ough its links with QFT and the impact of Stochastic Calcu- lus of Variations of P. Malliavin. Although the latter deals essentially with the regularity of the laws of random varia- bles defined on the Wiener space, the book focuses on quite different subjects, i.e. independence, Ramer's theorem, etc. First year graduate level in functional analysis and theory of stochastic processes is required (stochastic integration with respect to Brownian motion, Ito formula etc). It can be taught as a 1-semester course as it is, or in 2 semesters adding preliminaries from the theory of stochastic processes It is a user-friendly introduction to Malliavin calculus!