Decoupling on the Wiener Space Related Besov Spaces and Applications to BSDEs

Decoupling on the Wiener Space  Related Besov Spaces  and Applications to BSDEs
Author: Stefan Geiss,Juha Ylinen
Publsiher: American Mathematical Society
Total Pages: 112
Release: 2021-11-16
Genre: Mathematics
ISBN: 9781470449353

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Decoupling on the Wiener Space Related Besov Spaces and Applications to BSDEs

Decoupling on the Wiener Space  Related Besov Spaces  and Applications to BSDEs
Author: Stefan Geiss (Mathematician),Juha Ylinen
Publsiher: Unknown
Total Pages: 135
Release: 2021
Genre: Besov spaces
ISBN: 1470467518

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A Proof that Artificial Neural Networks Overcome the Curse of Dimensionality in the Numerical Approximation of Black Scholes Partial Differential Equations

A Proof that Artificial Neural Networks Overcome the Curse of Dimensionality in the Numerical Approximation of Black   Scholes Partial Differential Equations
Author: Philipp Grohs,Fabian Hornung,Arnulf Jentzen,Philippe von Wurstemberger
Publsiher: American Mathematical Society
Total Pages: 106
Release: 2023-04-07
Genre: Mathematics
ISBN: 9781470456320

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Backward Stochastic Differential Equations

Backward Stochastic Differential Equations
Author: N El Karoui,Laurent Mazliak
Publsiher: CRC Press
Total Pages: 236
Release: 1997-01-17
Genre: Mathematics
ISBN: 0582307333

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This book presents the texts of seminars presented during the years 1995 and 1996 at the Université Paris VI and is the first attempt to present a survey on this subject. Starting from the classical conditions for existence and unicity of a solution in the most simple case-which requires more than basic stochartic calculus-several refinements on the hypotheses are introduced to obtain more general results.

Stochastic Integration by Parts and Functional It Calculus

Stochastic Integration by Parts and Functional It   Calculus
Author: Vlad Bally,Lucia Caramellino,Rama Cont
Publsiher: Birkhäuser
Total Pages: 208
Release: 2016-03-11
Genre: Mathematics
ISBN: 9783319271286

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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 Itô Calculus, a non-anticipative functional calculus that extends the classical Itô 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.

Differentiable Measures and the Malliavin Calculus

Differentiable Measures and the Malliavin Calculus
Author: Vladimir Igorevich Bogachev
Publsiher: American Mathematical Soc.
Total Pages: 506
Release: 2010-07-21
Genre: Mathematics
ISBN: 9780821849934

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This book provides the reader with the principal concepts and results related to differential properties of measures on infinite dimensional spaces. In the finite dimensional case such properties are described in terms of densities of measures with respect to Lebesgue measure. In the infinite dimensional case new phenomena arise. For the first time a detailed account is given of the theory of differentiable measures, initiated by S. V. Fomin in the 1960s; since then the method has found many various important applications. Differentiable properties are described for diverse concrete classes of measures arising in applications, for example, Gaussian, convex, stable, Gibbsian, and for distributions of random processes. Sobolev classes for measures on finite and infinite dimensional spaces are discussed in detail. Finally, we present the main ideas and results of the Malliavin calculus--a powerful method to study smoothness properties of the distributions of nonlinear functionals on infinite dimensional spaces with measures. The target readership includes mathematicians and physicists whose research is related to measures on infinite dimensional spaces, distributions of random processes, and differential equations in infinite dimensional spaces. The book includes an extensive bibliography on the subject.

Foundations of Computational Mathematics

Foundations of Computational Mathematics
Author: Ronald A. DeVore,Arieh Iserles,Endre Süli
Publsiher: Cambridge University Press
Total Pages: 418
Release: 2001-05-17
Genre: Mathematics
ISBN: 0521003490

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Collection of papers by leading researchers in computational mathematics, suitable for graduate students and researchers.

Frontiers in Stochastic Analysis BSDEs SPDEs and their Applications

Frontiers in Stochastic Analysis   BSDEs  SPDEs and their Applications
Author: Samuel N. Cohen,István Gyöngy,Gonҫalo dos Reis,David Siska,Łukasz Szpruch
Publsiher: Springer Nature
Total Pages: 300
Release: 2019-08-31
Genre: Mathematics
ISBN: 9783030222857

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This collection of selected, revised and extended contributions resulted from a Workshop on BSDEs, SPDEs and their Applications that took place in Edinburgh, Scotland, July 2017 and included the 8th World Symposium on BSDEs. The volume addresses recent advances involving backward stochastic differential equations (BSDEs) and stochastic partial differential equations (SPDEs). These equations are of fundamental importance in modelling of biological, physical and economic systems, and underpin many problems in control of random systems, mathematical finance, stochastic filtering and data assimilation. The papers in this volume seek to understand these equations, and to use them to build our understanding in other areas of mathematics. This volume will be of interest to those working at the forefront of modern probability theory, both established researchers and graduate students.