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Titlebook: Continuous Martingales and Brownian Motion; Daniel Revuz,Marc Yor Book 19911st edition Springer-Verlag Berlin Heidelberg 1991 Brownian mot

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書目名稱Continuous Martingales and Brownian Motion
編輯Daniel Revuz,Marc Yor
視頻videohttp://file.papertrans.cn/238/237008/237008.mp4
叢書名稱Grundlehren der mathematischen Wissenschaften
圖書封面Titlebook: Continuous Martingales and Brownian Motion;  Daniel Revuz,Marc Yor Book 19911st edition Springer-Verlag Berlin Heidelberg 1991 Brownian mot
描述This book focuses on the probabilistic theory ofBrownian motion. This is a good topic to center a discussion around because Brownian motion is in the intersec- tioll of many fundamental classes of processes. It is a continuous martingale, a Gaussian process, a Markov process or more specifically a process with in- dependent increments; it can actually be defined, up to simple transformations, as the real-valued, centered process with independent increments and continuous paths. It is therefore no surprise that a vast array of techniques may be success- fully applied to its study and we, consequently, chose to organize the book in the following way. After a first chapter where Brownian motion is introduced, each of the following ones is devoted to a new technique or notion and to some of its applications to Brownian motion. Among these techniques, two are of para- mount importance: stochastic calculus, the use ofwhich pervades the whole book and the powerful excursion theory, both of which are introduced in a self- contained fashion and with a minimum of apparatus. They have made much easier the proofs of many results found in the epoch-making book of It? and McKean: Diffusion Proce
出版日期Book 19911st edition
關(guān)鍵詞Brownian motion; Functionals; Generator; Martingal; Martingale; brownsche Bewegung; diffusion; ergodic theo
版次1
doihttps://doi.org/10.1007/978-3-662-21726-9
isbn_ebook978-3-662-21726-9Series ISSN 0072-7830 Series E-ISSN 2196-9701
issn_series 0072-7830
copyrightSpringer-Verlag Berlin Heidelberg 1991
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Stochastic Differential Equations,al martingale, its exponential .(.) satisfies the equality.this can be stated: .(.) is a solution to the stochastic differential equation.which may be written in differential form.We have even seen (Exercise (3.10) Chap. IV) that .(M. is the only solution to this equation. Likewise we saw in Sect. 2
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Grundlagen der WirtschaftspolitikIn this chapter, we review a few basic facts, mainly from integration and classical probability theories, which will be used throughout the book without further ado. Some other prerequisites, usually from calculus, which will be used in some special parts are collected in the Appendix at the end of the book.
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Schule, Kunstgewerbe, Weltausstellung,With It?’s formula, we saw how ..-functions operate on continuous semi-martingales. We now extend this to convex functions, thus introducing the important notion of local time.
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