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Levy matters IVestimation for discre...

Belomestny, Denis.

Levy matters IVestimation for discretely observed Levy processes /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Levy matters IVby Denis Belomestny ... [et al.].
Reminder of title:	estimation for discretely observed Levy processes /
other author:	Belomestny, Denis.
Published:	Cham :Springer International Publishing :2015.
Description:	xv, 286 p. :ill., digital ;24 cm.
Contained By:	Springer eBooks
Subject:	Levy processes.
Online resource:	http://dx.doi.org/10.1007/978-3-319-12373-8
ISBN:	9783319123738 (electronic bk.)

Levy matters IVestimation for discretely observed Levy processes /
Levy matters IVestimation for discretely observed Levy processes /[electronic resource] :by Denis Belomestny ... [et al.]. - Cham :Springer International Publishing :2015. - xv, 286 p. :ill., digital ;24 cm. - Lecture notes in mathematics,21280075-8434 ;. - Lecture notes in mathematics ;2035..

Estimation and calibration of Levy models via Fourier methods -- Adaptive Estimation for Levy processes -- Parametric estimation of Levy processes.

The aim of this volume is to provide an extensive account of the most recent advances in statistics for discretely observed Levy processes. These days, statistics for stochastic processes is a lively topic, driven by the needs of various fields of application, such as finance, the biosciences, and telecommunication. The three chapters of this volume are completely dedicated to the estimation of Levy processes, and are written by experts in the field. The first chapter by Denis Belomestny and Markus Reiss treats the low frequency situation, and estimation methods are based on the empirical characteristic function. The second chapter by Fabienne Comte and Valery Genon-Catalon is dedicated to non-parametric estimation mainly covering the high-frequency data case. A distinctive feature of this part is the construction of adaptive estimators, based on deconvolution or projection or kernel methods. The last chapter by Hiroki Masuda considers the parametric situation. The chapters cover the main aspects of the estimation of discretely observed Levy processes, when the observation scheme is regular, from an up-to-date viewpoint.

ISBN: 9783319123738 (electronic bk.)

Standard No.: 10.1007/978-3-319-12373-8doiSubjects--Topical Terms:

205891
Levy processes.

LC Class. No.: QA274.73

Dewey Class. No.: 519.2

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505 0 $a Estimation and calibration of Levy models via Fourier methods -- Adaptive Estimation for Levy processes -- Parametric estimation of Levy processes.
520 $a The aim of this volume is to provide an extensive account of the most recent advances in statistics for discretely observed Levy processes. These days, statistics for stochastic processes is a lively topic, driven by the needs of various fields of application, such as finance, the biosciences, and telecommunication. The three chapters of this volume are completely dedicated to the estimation of Levy processes, and are written by experts in the field. The first chapter by Denis Belomestny and Markus Reiss treats the low frequency situation, and estimation methods are based on the empirical characteristic function. The second chapter by Fabienne Comte and Valery Genon-Catalon is dedicated to non-parametric estimation mainly covering the high-frequency data case. A distinctive feature of this part is the construction of adaptive estimators, based on deconvolution or projection or kernel methods. The last chapter by Hiroki Masuda considers the parametric situation. The chapters cover the main aspects of the estimation of discretely observed Levy processes, when the observation scheme is regular, from an up-to-date viewpoint.
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