Stochastic Analysis in Discrete and Continuous Settings

This book PDF is perfect for those who love Mathematics genre, written by Nicolas Privault and published by Springer which was released on 14 July 2009 with total hardcover pages 282. You could read this book directly on your devices with pdf, epub and kindle format, check detail and related Stochastic Analysis in Discrete and Continuous Settings books below.

Stochastic Analysis in Discrete and Continuous Settings
Author : Nicolas Privault
File Size : 51,8 Mb
Publisher : Springer
Language : English
Release Date : 14 July 2009
ISBN : 9783642023804
Pages : 282 pages
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Stochastic Analysis in Discrete and Continuous Settings by Nicolas Privault Book PDF Summary

This monograph is an introduction to some aspects of stochastic analysis in the framework of normal martingales, in both discrete and continuous time. The text is mostly self-contained, except for Section 5.7 that requires some background in geometry, and should be accessible to graduate students and researchers having already received a basic training in probability. Prereq- sites are mostly limited to a knowledge of measure theory and probability, namely?-algebras,expectations,andconditionalexpectations.Ashortint- duction to stochastic calculus for continuous and jump processes is given in Chapter 2 using normal martingales, whose predictable quadratic variation is the Lebesgue measure. There already exists several books devoted to stochastic analysis for c- tinuous di?usion processes on Gaussian and Wiener spaces, cf. e.g. [51], [63], [65], [72], [83], [84], [92], [128], [134], [143], [146], [147]. The particular f- ture of this text is to simultaneously consider continuous processes and jump processes in the uni?ed framework of normal martingales.

Stochastic Analysis in Discrete and Continuous Settings

This monograph is an introduction to some aspects of stochastic analysis in the framework of normal martingales, in both discrete and continuous time. The text is mostly self-contained, except for Section 5.7 that requires some background in geometry, and should be accessible to graduate students and researchers having already received a

Get Book
Stochastic Analysis In Discrete And Continuous Settings

Download or read online Stochastic Analysis In Discrete And Continuous Settings written by Anonim, published by Springer which was released on 2009. Get Stochastic Analysis In Discrete And Continuous Settings Books now! Available in PDF, ePub and Kindle.

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The articles in this collection are a sampling of some of the research presented during the conference “Stochastic Analysis and Related Topics”, held in May of 2015 at Purdue University in honor of the 60th birthday of Rodrigo Bañuelos. A wide variety of topics in probability theory is covered in

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Stochastic Analysis for Poisson Point Processes

Stochastic geometry is the branch of mathematics that studies geometric structures associated with random configurations, such as random graphs, tilings and mosaics. Due to its close ties with stereology and spatial statistics, the results in this area are relevant for a large number of important applications, e.g. to the

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Stochastic Calculus of Variations

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

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Wiener Chaos  Moments  Cumulants and Diagrams

The concept of Wiener chaos generalizes to an infinite-dimensional setting the properties of orthogonal polynomials associated with probability distributions on the real line. It plays a crucial role in modern probability theory, with applications ranging from Malliavin calculus to stochastic differential equations and from probabilistic approximations to mathematical finance. This

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Stochastic Control in Discrete and Continuous Time

This book contains an introduction to three topics in stochastic control: discrete time stochastic control, i. e. , stochastic dynamic programming (Chapter 1), piecewise - terministic control problems (Chapter 3), and control of Ito diffusions (Chapter 4). The chapters include treatments of optimal stopping problems. An Appendix - calls material from elementary probability theory

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