Methods of Optimal Statistical Decisions, Optimal Control, and Stochastic Differential Equations

Methods of Optimal Statistical Decisions, Optimal Control, and Stochastic Differential Equations
Author: Ellida M. Khazen
Publisher: Xlibris Corporation
Total Pages: 320
Release: 2009-11-16
Genre: Education
ISBN: 1462807178

This book provides the reader with some insight into the mathematical models of random processes with continuous time, stochastic differential equations and stochastic integrals. An advanced development of the mathematical methods of optimal statistical decisions, statistical sequential analysis, and informational estimation of risks, and new methods and solutions to the important problems of the theory of optimal control are presented. The new original results obtained by this author and published shortly in her numerous scientific-research papers are presented in a systematic way in this book. The book is intended for engineers, students, post-graduate students, and scientist researchers. The presentation of the material is accessible to engineers.

Optimal Stochastic Control, Stochastic Target Problems, and Backward SDE

Optimal Stochastic Control, Stochastic Target Problems, and Backward SDE
Author: Nizar Touzi
Publisher: Springer Science & Business Media
Total Pages: 219
Release: 2012-09-25
Genre: Mathematics
ISBN: 1461442869

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.​

Stochastic Optimal Control in Infinite Dimension

Stochastic Optimal Control in Infinite Dimension
Author: Giorgio Fabbri
Publisher: Springer
Total Pages: 928
Release: 2017-06-22
Genre: Mathematics
ISBN: 3319530674

Providing an introduction to stochastic optimal control in infinite dimension, this book gives a complete account of the theory of second-order HJB equations in infinite-dimensional Hilbert spaces, focusing on its applicability to associated stochastic optimal control problems. It features a general introduction to optimal stochastic control, including basic results (e.g. the dynamic programming principle) with proofs, and provides examples of applications. A complete and up-to-date exposition of the existing theory of viscosity solutions and regular solutions of second-order HJB equations in Hilbert spaces is given, together with an extensive survey of other methods, with a full bibliography. In particular, Chapter 6, written by M. Fuhrman and G. Tessitore, surveys the theory of regular solutions of HJB equations arising in infinite-dimensional stochastic control, via BSDEs. The book is of interest to both pure and applied researchers working in the control theory of stochastic PDEs, and in PDEs in infinite dimension. Readers from other fields who want to learn the basic theory will also find it useful. The prerequisites are: standard functional analysis, the theory of semigroups of operators and its use in the study of PDEs, some knowledge of the dynamic programming approach to stochastic optimal control problems in finite dimension, and the basics of stochastic analysis and stochastic equations in infinite-dimensional spaces.

Applied Stochastic Differential Equations

Applied Stochastic Differential Equations
Author: Simo Särkkä
Publisher: Cambridge University Press
Total Pages: 327
Release: 2019-05-02
Genre: Business & Economics
ISBN: 1316510085

With this hands-on introduction readers will learn what SDEs are all about and how they should use them in practice.

Random Evolutions and their Applications

Random Evolutions and their Applications
Author: Anatoly Swishchuk
Publisher: Springer Science & Business Media
Total Pages: 310
Release: 2013-03-14
Genre: Mathematics
ISBN: 9401595984

The book is devoted to the new trends in random evolutions and their various applications to stochastic evolutionary sytems (SES). Such new developments as the analogue of Dynkin's formulae, boundary value problems, stochastic stability and optimal control of random evolutions, stochastic evolutionary equations driven by martingale measures are considered. The book also contains such new trends in applied probability as stochastic models of financial and insurance mathematics in an incomplete market. In the famous classical financial mathematics Black-Scholes model of a (B,S) market for securities prices, which is used for the description of the evolution of bonds and stocks prices and also for their derivatives, such as options, futures, forward contracts, etc., it is supposed that the dynamic of bonds and stocks prices are set by a linear differential and linear stochastic differential equations, respectively, with interest rate, appreciation rate and volatility such that they are predictable processes. Also, in the Arrow-Debreu economy, the securities prices which support a Radner dynamic equilibrium are a combination of an Ito process and a random point process, with the all coefficients and jumps being predictable processes.

Backward Stochastic Differential Equations

Backward Stochastic Differential Equations
Author: N El Karoui
Publisher: CRC Press
Total Pages: 236
Release: 1997-01-17
Genre: Mathematics
ISBN: 9780582307339

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.

Statistics of Random Processes II

Statistics of Random Processes II
Author: Robert Shevilevich Lipt︠s︡er
Publisher: Springer Science & Business Media
Total Pages: 428
Release: 2001
Genre: Mathematics
ISBN: 9783540639282

"Written by two renowned experts in the field, the books under review contain a thorough and insightful treatment of the fundamental underpinnings of various aspects of stochastic processes as well as a wide range of applications. Providing clear exposition, deep mathematical results, and superb technical representation, they are masterpieces of the subject of stochastic analysis and nonlinear filtering....These books...will become classics." --SIAM REVIEW

Dynamic Optimization, Second Edition

Dynamic Optimization, Second Edition
Author: Morton I. Kamien
Publisher: Courier Corporation
Total Pages: 402
Release: 2013-04-17
Genre: Mathematics
ISBN: 0486310280

Since its initial publication, this text has defined courses in dynamic optimization taught to economics and management science students. The two-part treatment covers the calculus of variations and optimal control. 1998 edition.

Optimal Control

Optimal Control
Author: Brian D. O. Anderson
Publisher: Courier Corporation
Total Pages: 465
Release: 2007-02-27
Genre: Technology & Engineering
ISBN: 0486457664

Numerous examples highlight this treatment of the use of linear quadratic Gaussian methods for control system design. It explores linear optimal control theory from an engineering viewpoint, with illustrations of practical applications. Key topics include loop-recovery techniques, frequency shaping, and controller reduction. Numerous examples and complete solutions. 1990 edition.