Stochastic Analysis, Stochastic Systems, And Applications To Finance, Tsoi Allanus Et Al

Автор: Shreve, Steven E.
Название: Stochastic Calculus for Finance II
ISBN: 0387401016 ISBN-13(EAN): 9780387401010
Издательство: Springer
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Цена: 8384.00 р.
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Описание: "A wonderful display of the use of mathematical probability to derive a large set of results from a small set of assumptions.

Автор: Gallager
Название: Stochastic Processes
ISBN: 1107039754 ISBN-13(EAN): 9781107039759
Издательство: Cambridge Academ
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Описание: This definitive textbook provides a solid introduction to stochastic processes, covering both theory and applications. It is written by one of the world`s leading information theorists, evolving over twenty years of graduate classroom teaching, and is accompanied by over 300 exercises, with online solutions for instructors.

Автор: Shreve
Название: Stochastic Calculus for Finance I
ISBN: 0387401008 ISBN-13(EAN): 9780387401003
Издательство: Springer
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Цена: 8384.00 р.
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Описание: Developed for the professional Master`s program in Computational Finance at Carnegie Mellon, the leading financial engineering program in the U.S. Has been tested in the classroom and revised over a period of several yearsExercises conclude every chapter;

Автор: Asmussen
Название: Stochastic Simulation: Algorithms and Analysis
ISBN: 038730679X ISBN-13(EAN): 9780387306797
Издательство: Springer
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Цена: 6981.00 р.
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Описание: Sampling-based computational methods have become a fundamental part of the numerical toolset of practitioners and researchers across an enormous number of different applied domains and academic disciplines. This book provides a broad treatment of such sampling-based methods , as well as accompanying mathematical analysis of the convergence properties of the methods discussed . The reach of the ideas is illustrated by discussing a wide range of applications and the models that have found wide usage. The first  half of the book focusses on general methods, whereas the second half discusses model-specific algorithms. Given the wide range of  examples, exercises and applications students, practitioners and researchers in  probability, statistics, operations research, economics, finance, engineering  as well as biology and chemistry and physics will find the book of value.  Soren Asmussen is Professor of Applied Probability at Aarhus University, Denmark and Peter Glynn is Thomas Ford Professor of  Engineering at Stanford University. 

Автор: Mou-Hsiung Chang
Название: Stochastic Control of Hereditary Systems and Applications
ISBN: 1441926054 ISBN-13(EAN): 9781441926050
Издательство: Springer
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Цена: 21661.00 р.
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Описание: This research monograph develops the Hamilton-Jacobi-Bellman theory, a very active research area. It is intended for researchers and advanced graduate students who have special interest in optimal control theory and applications of stochastic hereditary systems.

Автор: Parzen, Emanuel
Название: Stochastic processes
ISBN: 0898714419 ISBN-13(EAN): 9780898714418
Издательство: Mare Nostrum (Eurospan)
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Цена: 9656.00 р.
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Описание: This introductory textbook explains how and why probability models are applied to scientific fields such as medicine, biology, physics, oceanography, economics, and psychology to solve problems about stochastic processes. It does not just show how a problem is solved but explains why by formulating questions and first steps in the solutions.

Автор: Kabanov Yuri, Pergamenshchikov Sergei
Название: Two-Scale Stochastic Systems / Asymptotic Analysis and Control
ISBN: 3540653325 ISBN-13(EAN): 9783540653325
Издательство: Springer
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Цена: 13974.00 р.
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Описание: Two-scale systems described by singularly perturbed SDEs have been the subject of ample literature. However, this new monograph develops subjects that were rarely addressed and could be given the collective description "Stochastic Tikhonov-Levinson theory and its applications." The book provides a mathematical apparatus designed to analyze the dynamic behaviour of a randomly perturbed system with fast and slow variables. In contrast to the deterministic Tikhonov-Levinson theory, the basic model is described in a more realistic way by stochastic differential equations. This leads to a number of new theoretical questions but simultaneously allows us to treat in a unified way a surprisingly wide spectrum of applications like fast modulations, approximate filtering, and stochastic approximation.