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Stochastic Calculus via Regularizations / by Francesco Russo, Pierre Vallois
(Bocconi & Springer Series, Mathematics, Statistics, Finance and Economics. ISSN:2039148X ; 11)

1st ed. 2022.
出版者 (Cham : Springer International Publishing : Imprint: Springer)
出版年 2022
大きさ XXXI, 638 p : online resource
著者標目 *Russo, Francesco author
Vallois, Pierre author
SpringerLink (Online service)
件 名 LCSH:Probabilities
LCSH:Stochastic analysis
LCSH:Mathematical analysis
FREE:Probability Theory
FREE:Stochastic Analysis
FREE:Analysis
一般注記 The book constitutes an introduction to stochastic calculus, stochastic differential equations and related topics such as Malliavin calculus. On the other hand it focuses on the techniques of stochastic integration and calculus via regularization initiated by the authors. The definitions relies on a smoothing procedure of the integrator process, they generalize the usual Itô and Stratonovich integrals for Brownian motion but the integrator could also not be a semimartingale and the integrand is allowed to be anticipating. The resulting calculus requires a simple formalism: nevertheless it entails pathwise techniques even though it takes into account randomness. It allows connecting different types of pathwise and non pathwise integrals such as Young, fractional, Skorohod integrals, enlargement of filtration and rough paths. The covariation, but also high order variations, play a fundamental role in the calculus via regularization, which can also be applied for irregular integrators. A large class of Gaussian processes, various generalizations of semimartingales such that Dirichlet and weak Dirichlet processes are revisited. Stochastic calculus via regularization has been successfully used in applications, for instance in robust finance and on modeling vortex filaments in turbulence. The book is addressed to PhD students and researchers in stochastic analysis and applications to various fields
HTTP:URL=https://doi.org/10.1007/978-3-031-09446-0
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電子ブック オンライン 電子ブック

Springer eBooks 9783031094460
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EB00222990

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データ種別 電子ブック
分 類 LCC:QA273.A1-274.9
DC23:519.2
書誌ID 4000986020
ISBN 9783031094460

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