Probability Methods for Approximations in Stochastic Control and for Elliptic Equations

Probability Methods for Approximations in Stochastic Control and for Elliptic Equations PDF Author: Kushner
Publisher: Academic Press
ISBN: 0080956386
Category : Computers
Languages : en
Pages : 263

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Book Description
Probability Methods for Approximations in Stochastic Control and for Elliptic Equations

Probability Methods for Approximations in Stochastic Control and for Elliptic Equations

Probability Methods for Approximations in Stochastic Control and for Elliptic Equations PDF Author: Kushner
Publisher: Academic Press
ISBN: 0080956386
Category : Computers
Languages : en
Pages : 263

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Book Description
Probability Methods for Approximations in Stochastic Control and for Elliptic Equations

Numerical Methods for Stochastic Control Problems in Continuous Time

Numerical Methods for Stochastic Control Problems in Continuous Time PDF Author: Harold Kushner
Publisher: Springer Science & Business Media
ISBN: 146130007X
Category : Mathematics
Languages : en
Pages : 480

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Book Description
Stochastic control is a very active area of research. This monograph, written by two leading authorities in the field, has been updated to reflect the latest developments. It covers effective numerical methods for stochastic control problems in continuous time on two levels, that of practice and that of mathematical development. It is broadly accessible for graduate students and researchers.

Optimal Stochastic Control, Stochastic Target Problems, and Backward SDE

Optimal Stochastic Control, Stochastic Target Problems, and Backward SDE PDF Author: Nizar Touzi
Publisher: Springer Science & Business Media
ISBN: 1461442869
Category : Mathematics
Languages : en
Pages : 219

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Book Description
This book collects some recent developments in stochastic control theory with applications to financial mathematics. We first address standard stochastic control problems from the viewpoint of the recently developed weak dynamic programming principle. A special emphasis is put on the regularity issues and, in particular, on the behavior of the value function near the boundary. We then provide a quick review of the main tools from viscosity solutions which allow to overcome all regularity problems. We next address the class of stochastic target problems which extends in a nontrivial way the standard stochastic control problems. Here the theory of viscosity solutions plays a crucial role in the derivation of the dynamic programming equation as the infinitesimal counterpart of the corresponding geometric dynamic programming equation. The various developments of this theory have been stimulated by applications in finance and by relevant connections with geometric flows. Namely, the second order extension was motivated by illiquidity modeling, and the controlled loss version was introduced following the problem of quantile hedging. The third part specializes to an overview of Backward stochastic differential equations, and their extensions to the quadratic case.​

Optimal Stopping and Free-Boundary Problems

Optimal Stopping and Free-Boundary Problems PDF Author: Goran Peskir
Publisher: Springer Science & Business Media
ISBN: 3764373903
Category : Mathematics
Languages : en
Pages : 515

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Book Description
This book discloses a fascinating connection between optimal stopping problems in probability and free-boundary problems. It focuses on key examples and the theory of optimal stopping is exposed at its basic principles in discrete and continuous time covering martingale and Markovian methods. Methods of solution explained range from change of time, space, and measure, to more recent ones such as local time-space calculus and nonlinear integral equations. A chapter on stochastic processes makes the material more accessible. The book will appeal to those wishing to master stochastic calculus via fundamental examples. Areas of application include financial mathematics, financial engineering, and mathematical statistics.

Backward Stochastic Differential Equations

Backward Stochastic Differential Equations PDF Author: N El Karoui
Publisher: CRC Press
ISBN: 9780582307339
Category : Mathematics
Languages : en
Pages : 236

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Book Description
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 Modeling and Control

Stochastic Modeling and Control PDF Author: Ivan Ivanov
Publisher: BoD – Books on Demand
ISBN: 9535108301
Category : Mathematics
Languages : en
Pages : 288

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Book Description
Stochastic control plays an important role in many scientific and applied disciplines including communications, engineering, medicine, finance and many others. It is one of the effective methods being used to find optimal decision-making strategies in applications. The book provides a collection of outstanding investigations in various aspects of stochastic systems and their behavior. The book provides a self-contained treatment on practical aspects of stochastic modeling and calculus including applications drawn from engineering, statistics, and computer science. Readers should be familiar with basic probability theory and have a working knowledge of stochastic calculus. PhD students and researchers in stochastic control will find this book useful.

Convex Analysis and Minimization Algorithms I

Convex Analysis and Minimization Algorithms I PDF Author: Jean-Baptiste Hiriart-Urruty
Publisher: Springer Science & Business Media
ISBN: 3662027968
Category : Mathematics
Languages : en
Pages : 432

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Book Description
Convex Analysis may be considered as a refinement of standard calculus, with equalities and approximations replaced by inequalities. As such, it can easily be integrated into a graduate study curriculum. Minimization algorithms, more specifically those adapted to non-differentiable functions, provide an immediate application of convex analysis to various fields related to optimization and operations research. These two topics making up the title of the book, reflect the two origins of the authors, who belong respectively to the academic world and to that of applications. Part I can be used as an introductory textbook (as a basis for courses, or for self-study); Part II continues this at a higher technical level and is addressed more to specialists, collecting results that so far have not appeared in books.

Stochastic Differential Systems, Stochastic Control Theory and Applications

Stochastic Differential Systems, Stochastic Control Theory and Applications PDF Author: Wendell Fleming
Publisher: Springer Science & Business Media
ISBN: 1461387620
Category : Mathematics
Languages : en
Pages : 601

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Book Description
This IMA Volume in Mathematics and its Applications STOCHASTIC DIFFERENTIAL SYSTEMS, STOCHASTIC CONTROL THEORY AND APPLICATIONS is the proceedings of a workshop which was an integral part of the 1986-87 IMA program on STOCHASTIC DIFFERENTIAL EQUATIONS AND THEIR APPLICATIONS. We are grateful to the Scientific Committee: Daniel Stroock (Chairman) WendeIl Flerning Theodore Harris Pierre-Louis Lions Steven Orey George Papanicolaou for planning and implementing an exciting and stimulating year-long program. We es pecially thank WendeIl Fleming and Pierre-Louis Lions for organizing an interesting and productive workshop in an area in which mathematics is beginning to make significant contributions to real-world problems. George R. Seil Hans Weinberger PREFACE This volume is the Proceedings of a Workshop on Stochastic Differential Systems, Stochastic Control Theory, and Applications held at IMA June 9-19,1986. The Workshop Program Commit tee consisted of W.H. Fleming and P.-L. Lions (co-chairmen), J. Baras, B. Hajek, J.M. Harrison, and H. Sussmann. The Workshop emphasized topics in the following four areas. (1) Mathematical theory of stochastic differential systems, stochastic control and nonlinear filtering for Markov diffusion processes. Connections with partial differential equations. (2) Applications of stochastic differential system theory, in engineering and management sci ence. Adaptive control of Markov processes. Advanced computational methods in stochas tic control and nonlinear filtering. (3) Stochastic scheduling, queueing networks, and related topics. Flow control, multiarm bandit problems, applications to problems of computer networks and scheduling of complex manufacturing operations.

Modern Trends in Controlled Stochastic Processes

Modern Trends in Controlled Stochastic Processes PDF Author: Alexey B. Piunovskiy
Publisher: Luniver Press
ISBN: 1905986300
Category : Mathematics
Languages : en
Pages : 342

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Book Description
World leading experts give their accounts of the modern mathematical models in the field: Markov Decision Processes, controlled diffusions, piece-wise deterministic processes etc, with a wide range of performance functionals. One of the aims is to give a general view on the state-of-the-art. The authors use Dynamic Programming, Convex Analytic Approach, several numerical methods, index-based approach and so on. Most chapters either contain well developed examples, or are entirely devoted to the application of the mathematical control theory to real life problems from such fields as Insurance, Portfolio Optimization and Information Transmission. The book will enable researchers, academics and research students to get a sense of novel results, concepts, models, methods, and applications of controlled stochastic processes.

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.