Read Books Online and Download eBooks, EPub, PDF, Mobi, Kindle, Text Full Free.
Approximation Theorems For Levy Driven Marcus Canonical Stochastic Differential Equations
Download Approximation Theorems For Levy Driven Marcus Canonical Stochastic Differential Equations full books in PDF, epub, and Kindle. Read online Approximation Theorems For Levy Driven Marcus Canonical Stochastic Differential Equations ebook anywhere anytime directly on your device. Fast Download speed and no annoying ads. We cannot guarantee that every ebooks is available!
Book Synopsis Approximation Theorems for Lévy-driven Marcus (canonical) Stochastic Differential Equations by : Sooppawat Thipyarat
Download or read book Approximation Theorems for Lévy-driven Marcus (canonical) Stochastic Differential Equations written by Sooppawat Thipyarat and published by . This book was released on 2024* with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this thesis, we consider the problem of the numerical approximation of the Marcus (canonical) stochastic differential equations (SDEs) driven by a Brownian motion and an independent the pure jump Lévy process. The numerical scheme used in this thesis is the non-linear discrete time approximation based on the Wong-Zakai approximation scheme. The main results of this thesis are presented in two parts. In the first part, we prove the uniform strong approximation theorem for solutions of the Marcus SDEs. This result is an extension of the approximation results known for Stratonovich SDEs driven by a Brownian motion. We also estimate the convergence rate of strong approximations. The approximation scheme requires the explicit knowledge of the increments of the pure jump Lévy process. In the second part, we apply the method suggested by Asmussen and Rosiński, and approximate the increments of the pure jump Lévy process by a sum of Gaussian and a compound Poisson random variables that can be simulated explicitly. Hence, we examine the weak and strong convergence of the modified Wong-Zakai approximations and also determine the convergence rates. We illustrate our results by a numerical example.
Book Synopsis Approximation Theorems of Wong-Zakai Type for Stochastic Differential Equations in Infinite Dimensions by : Krystyna Twardowska
Download or read book Approximation Theorems of Wong-Zakai Type for Stochastic Differential Equations in Infinite Dimensions written by Krystyna Twardowska and published by . This book was released on 1993 with total page 64 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Lévy Processes and Stochastic Calculus by : David Applebaum
Download or read book Lévy Processes and Stochastic Calculus written by David Applebaum and published by Cambridge University Press. This book was released on 2009-04-30 with total page 461 pages. Available in PDF, EPUB and Kindle. Book excerpt: Lévy processes form a wide and rich class of random process, and have many applications ranging from physics to finance. Stochastic calculus is the mathematics of systems interacting with random noise. Here, the author ties these two subjects together, beginning with an introduction to the general theory of Lévy processes, then leading on to develop the stochastic calculus for Lévy processes in a direct and accessible way. This fully revised edition now features a number of new topics. These include: regular variation and subexponential distributions; necessary and sufficient conditions for Lévy processes to have finite moments; characterisation of Lévy processes with finite variation; Kunita's estimates for moments of Lévy type stochastic integrals; new proofs of Ito representation and martingale representation theorems for general Lévy processes; multiple Wiener-Lévy integrals and chaos decomposition; an introduction to Malliavin calculus; an introduction to stability theory for Lévy-driven SDEs.
Book Synopsis On the Dynamics of Marcus Type Stochastic Differential Equations by : Kai Kümmel
Download or read book On the Dynamics of Marcus Type Stochastic Differential Equations written by Kai Kümmel and published by . This book was released on 2016 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Numerical Approximations of Stochastic Differential Equations with Non-Globally Lipschitz Continuous Coefficients by : Martin Hutzenthaler
Download or read book Numerical Approximations of Stochastic Differential Equations with Non-Globally Lipschitz Continuous Coefficients written by Martin Hutzenthaler and published by American Mathematical Soc.. This book was released on 2015-06-26 with total page 112 pages. Available in PDF, EPUB and Kindle. Book excerpt: Many stochastic differential equations (SDEs) in the literature have a superlinearly growing nonlinearity in their drift or diffusion coefficient. Unfortunately, moments of the computationally efficient Euler-Maruyama approximation method diverge for these SDEs in finite time. This article develops a general theory based on rare events for studying integrability properties such as moment bounds for discrete-time stochastic processes. Using this approach, the authors establish moment bounds for fully and partially drift-implicit Euler methods and for a class of new explicit approximation methods which require only a few more arithmetical operations than the Euler-Maruyama method. These moment bounds are then used to prove strong convergence of the proposed schemes. Finally, the authors illustrate their results for several SDEs from finance, physics, biology and chemistry.
Book Synopsis Taylor Approximations for Stochastic Partial Differential Equations by : Arnulf Jentzen
Download or read book Taylor Approximations for Stochastic Partial Differential Equations written by Arnulf Jentzen and published by SIAM. This book was released on 2011-01-01 with total page 234 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents a systematic theory of Taylor expansions of evolutionary-type stochastic partial differential equations (SPDEs). The authors show how Taylor expansions can be used to derive higher order numerical methods for SPDEs, with a focus on pathwise and strong convergence. In the case of multiplicative noise, the driving noise process is assumed to be a cylindrical Wiener process, while in the case of additive noise the SPDE is assumed to be driven by an arbitrary stochastic process with Hl̲der continuous sample paths. Recent developments on numerical methods for random and stochastic ordinary differential equations are also included since these are relevant for solving spatially discretised SPDEs as well as of interest in their own right. The authors include the proof of an existence and uniqueness theorem under general assumptions on the coefficients as well as regularity estimates in an appendix.
Book Synopsis Lectures on Stochastic Differential Equations and Malliavin Calculus by : Shinzo Watanabe
Download or read book Lectures on Stochastic Differential Equations and Malliavin Calculus written by Shinzo Watanabe and published by . This book was released on 1984 with total page 140 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Stochastic Differential Equations by : Bernt Karsten Øksendal
Download or read book Stochastic Differential Equations written by Bernt Karsten Øksendal and published by Springer Science & Business Media. This book was released on 1998 with total page 348 pages. Available in PDF, EPUB and Kindle. Book excerpt: The new edition of this bestselling book introduces the basic theory of stochastic calculus and its applications. Examples are given throughout to illustrate the theory and to show its importance for many applications that arise in areas such as economics, finance, physics, and biology. A new chapter on mathematical finance is included.
Book Synopsis Proceedings of the Japan Academy by : Nihon Gakushiin
Download or read book Proceedings of the Japan Academy written by Nihon Gakushiin and published by . This book was released on 2001 with total page 282 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Brownian Motion, Martingales, and Stochastic Calculus by : Jean-François Le Gall
Download or read book Brownian Motion, Martingales, and Stochastic Calculus written by Jean-François Le Gall and published by Springer. This book was released on 2016-04-28 with total page 282 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book offers a rigorous and self-contained presentation of stochastic integration and stochastic calculus within the general framework of continuous semimartingales. The main tools of stochastic calculus, including Itô’s formula, the optional stopping theorem and Girsanov’s theorem, are treated in detail alongside many illustrative examples. The book also contains an introduction to Markov processes, with applications to solutions of stochastic differential equations and to connections between Brownian motion and partial differential equations. The theory of local times of semimartingales is discussed in the last chapter. Since its invention by Itô, stochastic calculus has proven to be one of the most important techniques of modern probability theory, and has been used in the most recent theoretical advances as well as in applications to other fields such as mathematical finance. Brownian Motion, Martingales, and Stochastic Calculus provides a strong theoretical background to the reader interested in such developments. Beginning graduate or advanced undergraduate students will benefit from this detailed approach to an essential area of probability theory. The emphasis is on concise and efficient presentation, without any concession to mathematical rigor. The material has been taught by the author for several years in graduate courses at two of the most prestigious French universities. The fact that proofs are given with full details makes the book particularly suitable for self-study. The numerous exercises help the reader to get acquainted with the tools of stochastic calculus.
Book Synopsis Approximations of Solutions of Stochastic Differential Equations Driven by Semimartingales by : P. Protter
Download or read book Approximations of Solutions of Stochastic Differential Equations Driven by Semimartingales written by P. Protter and published by . This book was released on 1983 with total page 45 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Quadrature for Path-dependent Functionals of Lévy-driven Stochastic Differential Equations by : Felix Heidenreich
Download or read book Quadrature for Path-dependent Functionals of Lévy-driven Stochastic Differential Equations written by Felix Heidenreich and published by . This book was released on 2012 with total page 111 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis A Course on Rough Paths by : Peter K. Friz
Download or read book A Course on Rough Paths written by Peter K. Friz and published by Springer Nature. This book was released on 2020-05-27 with total page 346 pages. Available in PDF, EPUB and Kindle. Book excerpt: With many updates and additional exercises, the second edition of this book continues to provide readers with a gentle introduction to rough path analysis and regularity structures, theories that have yielded many new insights into the analysis of stochastic differential equations, and, most recently, stochastic partial differential equations. Rough path analysis provides the means for constructing a pathwise solution theory for stochastic differential equations which, in many respects, behaves like the theory of deterministic differential equations and permits a clean break between analytical and probabilistic arguments. Together with the theory of regularity structures, it forms a robust toolbox, allowing the recovery of many classical results without having to rely on specific probabilistic properties such as adaptedness or the martingale property. Essentially self-contained, this textbook puts the emphasis on ideas and short arguments, rather than aiming for the strongest possible statements. A typical reader will have been exposed to upper undergraduate analysis and probability courses, with little more than Itô-integration against Brownian motion required for most of the text. From the reviews of the first edition: "Can easily be used as a support for a graduate course ... Presents in an accessible way the unique point of view of two experts who themselves have largely contributed to the theory" - Fabrice Baudouin in the Mathematical Reviews "It is easy to base a graduate course on rough paths on this ... A researcher who carefully works her way through all of the exercises will have a very good impression of the current state of the art" - Nicolas Perkowski in Zentralblatt MATH
Book Synopsis Combinatorial Stochastic Processes by : Jim Pitman
Download or read book Combinatorial Stochastic Processes written by Jim Pitman and published by Springer Science & Business Media. This book was released on 2006-05-11 with total page 257 pages. Available in PDF, EPUB and Kindle. Book excerpt: The purpose of this text is to bring graduate students specializing in probability theory to current research topics at the interface of combinatorics and stochastic processes. There is particular focus on the theory of random combinatorial structures such as partitions, permutations, trees, forests, and mappings, and connections between the asymptotic theory of enumeration of such structures and the theory of stochastic processes like Brownian motion and Poisson processes.
Download or read book Brownian Motion written by Peter Mörters and published by Cambridge University Press. This book was released on 2010-03-25 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: This eagerly awaited textbook covers everything the graduate student in probability wants to know about Brownian motion, as well as the latest research in the area. Starting with the construction of Brownian motion, the book then proceeds to sample path properties like continuity and nowhere differentiability. Notions of fractal dimension are introduced early and are used throughout the book to describe fine properties of Brownian paths. The relation of Brownian motion and random walk is explored from several viewpoints, including a development of the theory of Brownian local times from random walk embeddings. Stochastic integration is introduced as a tool and an accessible treatment of the potential theory of Brownian motion clears the path for an extensive treatment of intersections of Brownian paths. An investigation of exceptional points on the Brownian path and an appendix on SLE processes, by Oded Schramm and Wendelin Werner, lead directly to recent research themes.
Book Synopsis Differentiable Measures and the Malliavin Calculus by : Vladimir Igorevich Bogachev
Download or read book Differentiable Measures and the Malliavin Calculus written by Vladimir Igorevich Bogachev and published by American Mathematical Soc.. This book was released on 2010-07-21 with total page 506 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis High-Dimensional Probability by : Roman Vershynin
Download or read book High-Dimensional Probability written by Roman Vershynin and published by Cambridge University Press. This book was released on 2018-09-27 with total page 299 pages. Available in PDF, EPUB and Kindle. Book excerpt: An integrated package of powerful probabilistic tools and key applications in modern mathematical data science.
