Stochastic Integration with Jumps

Stochastic Integration with Jumps PDF Author: Klaus Bichteler
Publisher: Cambridge University Press
ISBN: 0521811295
Category : Mathematics
Languages : en
Pages : 517

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Book Description
The complete theory of stochastic differential equations driven by jumps, their stability, and numerical approximation theories.

Stochastic Integration with Jumps

Stochastic Integration with Jumps PDF Author: Klaus Bichteler
Publisher: Cambridge University Press
ISBN: 0521811295
Category : Mathematics
Languages : en
Pages : 517

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Book Description
The complete theory of stochastic differential equations driven by jumps, their stability, and numerical approximation theories.

Stochastic Integration with Jumps

Stochastic Integration with Jumps PDF Author: Klaus Bichteler
Publisher:
ISBN: 9780511020735
Category : MATHEMATICS
Languages : en
Pages : 517

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Book Description
The complete theory of stochastic differential equations driven by jumps, their stability, and numerical approximation theories.

Stochastic Calculus of Variations

Stochastic Calculus of Variations PDF Author: Yasushi Ishikawa
Publisher: Walter de Gruyter GmbH & Co KG
ISBN: 3110392321
Category : Mathematics
Languages : en
Pages : 362

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Book Description
This monograph is a concise introduction to the stochastic calculus of variations (also known as Malliavin calculus) for processes with jumps. It is written for researchers and graduate students who are interested in Malliavin calculus for jump processes. In this book "processes with jumps" includes both pure jump processes and jump-diffusions. The author provides many results on this topic in a self-contained way; this also applies to stochastic differential equations (SDEs) "with jumps". The book also contains some applications of the stochastic calculus for processes with jumps to the control theory and mathematical finance. Namely, asymptotic expansions functionals related with financial assets of jump-diffusion are provided based on the theory of asymptotic expansion on the Wiener–Poisson space. Solving the Hamilton–Jacobi–Bellman (HJB) equation of integro-differential type is related with solving the classical Merton problem and the Ramsey theory. The field of jump processes is nowadays quite wide-ranging, from the Lévy processes to SDEs with jumps. Recent developments in stochastic analysis have enabled us to express various results in a compact form. Up to now, these topics were rarely discussed in a monograph. Contents: Preface Preface to the second edition Introduction Lévy processes and Itô calculus Perturbations and properties of the probability law Analysis of Wiener–Poisson functionals Applications Appendix Bibliography List of symbols Index

PDE and Martingale Methods in Option Pricing

PDE and Martingale Methods in Option Pricing PDF Author: Andrea Pascucci
Publisher: Springer Science & Business Media
ISBN: 8847017815
Category : Mathematics
Languages : en
Pages : 727

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Book Description
This book offers an introduction to the mathematical, probabilistic and numerical methods used in the modern theory of option pricing. The text is designed for readers with a basic mathematical background. The first part contains a presentation of the arbitrage theory in discrete time. In the second part, the theories of stochastic calculus and parabolic PDEs are developed in detail and the classical arbitrage theory is analyzed in a Markovian setting by means of of PDEs techniques. After the martingale representation theorems and the Girsanov theory have been presented, arbitrage pricing is revisited in the martingale theory optics. General tools from PDE and martingale theories are also used in the analysis of volatility modeling. The book also contains an Introduction to Lévy processes and Malliavin calculus. The last part is devoted to the description of the numerical methods used in option pricing: Monte Carlo, binomial trees, finite differences and Fourier transform.

Stochastic Integration and Differential Equations

Stochastic Integration and Differential Equations PDF Author: Philip Protter
Publisher: Springer
ISBN: 3662100614
Category : Mathematics
Languages : en
Pages : 430

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Book Description
It has been 15 years since the first edition of Stochastic Integration and Differential Equations, A New Approach appeared, and in those years many other texts on the same subject have been published, often with connections to applications, especially mathematical finance. Yet in spite of the apparent simplicity of approach, none of these books has used the functional analytic method of presenting semimartingales and stochastic integration. Thus a 2nd edition seems worthwhile and timely, though it is no longer appropriate to call it "a new approach". The new edition has several significant changes, most prominently the addition of exercises for solution. These are intended to supplement the text, but lemmas needed in a proof are never relegated to the exercises. Many of the exercises have been tested by graduate students at Purdue and Cornell Universities. Chapter 3 has been completely redone, with a new, more intuitive and simultaneously elementary proof of the fundamental Doob-Meyer decomposition theorem, the more general version of the Girsanov theorem due to Lenglart, the Kazamaki-Novikov criteria for exponential local martingales to be martingales, and a modern treatment of compensators. Chapter 4 treats sigma martingales (important in finance theory) and gives a more comprehensive treatment of martingale representation, including both the Jacod-Yor theory and Emery’s examples of martingales that actually have martingale representation (thus going beyond the standard cases of Brownian motion and the compensated Poisson process). New topics added include an introduction to the theory of the expansion of filtrations, a treatment of the Fefferman martingale inequality, and that the dual space of the martingale space H^1 can be identified with BMO martingales. Solutions to selected exercises are available at the web site of the author, with current URL http://www.orie.cornell.edu/~protter/books.html.

Jump SDEs and the Study of Their Densities

Jump SDEs and the Study of Their Densities PDF Author: Arturo Kohatsu-Higa
Publisher: Springer
ISBN: 9813297417
Category : Mathematics
Languages : en
Pages : 355

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Book Description
The present book deals with a streamlined presentation of Lévy processes and their densities. It is directed at advanced undergraduates who have already completed a basic probability course. Poisson random variables, exponential random variables, and the introduction of Poisson processes are presented first, followed by the introduction of Poisson random measures in a simple case. With these tools the reader proceeds gradually to compound Poisson processes, finite variation Lévy processes and finally one-dimensional stable cases. This step-by-step progression guides the reader into the construction and study of the properties of general Lévy processes with no Brownian component. In particular, in each case the corresponding Poisson random measure, the corresponding stochastic integral, and the corresponding stochastic differential equations (SDEs) are provided. The second part of the book introduces the tools of the integration by parts formula for jump processes in basic settings and first gradually provides the integration by parts formula in finite-dimensional spaces and gives a formula in infinite dimensions. These are then applied to stochastic differential equations in order to determine the existence and some properties of their densities. As examples, instances of the calculations of the Greeks in financial models with jumps are shown. The final chapter is devoted to the Boltzmann equation.

Lévy Processes and Stochastic Calculus

Lévy Processes and Stochastic Calculus PDF Author: David Applebaum
Publisher: Cambridge University Press
ISBN: 1139477986
Category : Mathematics
Languages : en
Pages : 461

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Book Description
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.

Applied Stochastic Control of Jump Diffusions

Applied Stochastic Control of Jump Diffusions PDF Author: Bernt Øksendal
Publisher: Springer Science & Business Media
ISBN: 3540698264
Category : Mathematics
Languages : en
Pages : 263

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Book Description
Here is a rigorous introduction to the most important and useful solution methods of various types of stochastic control problems for jump diffusions and its applications. Discussion includes the dynamic programming method and the maximum principle method, and their relationship. The text emphasises real-world applications, primarily in finance. Results are illustrated by examples, with end-of-chapter exercises including complete solutions. The 2nd edition adds a chapter on optimal control of stochastic partial differential equations driven by Lévy processes, and a new section on optimal stopping with delayed information. Basic knowledge of stochastic analysis, measure theory and partial differential equations is assumed.

Stochastic Integration in Banach Spaces

Stochastic Integration in Banach Spaces PDF Author: Vidyadhar Mandrekar
Publisher: Springer
ISBN: 3319128531
Category : Mathematics
Languages : en
Pages : 213

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Book Description
Considering Poisson random measures as the driving sources for stochastic (partial) differential equations allows us to incorporate jumps and to model sudden, unexpected phenomena. By using such equations the present book introduces a new method for modeling the states of complex systems perturbed by random sources over time, such as interest rates in financial markets or temperature distributions in a specific region. It studies properties of the solutions of the stochastic equations, observing the long-term behavior and the sensitivity of the solutions to changes in the initial data. The authors consider an integration theory of measurable and adapted processes in appropriate Banach spaces as well as the non-Gaussian case, whereas most of the literature only focuses on predictable settings in Hilbert spaces. The book is intended for graduate students and researchers in stochastic (partial) differential equations, mathematical finance and non-linear filtering and assumes a knowledge of the required integration theory, existence and uniqueness results and stability theory. The results will be of particular interest to natural scientists and the finance community. Readers should ideally be familiar with stochastic processes and probability theory in general, as well as functional analysis and in particular the theory of operator semigroups. ​

Applied Stochastic Processes and Control for Jump-Diffusions

Applied Stochastic Processes and Control for Jump-Diffusions PDF Author: Floyd B. Hanson
Publisher: SIAM
ISBN: 9780898718638
Category : Mathematics
Languages : en
Pages : 472

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Book Description
This self-contained, practical, entry-level text integrates the basic principles of applied mathematics, applied probability, and computational science for a clear presentation of stochastic processes and control for jump diffusions in continuous time. The author covers the important problem of controlling these systems and, through the use of a jump calculus construction, discusses the strong role of discontinuous and nonsmooth properties versus random properties in stochastic systems.