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Levy matters IV[electronic resource]...

Belomestny, Denis.

Levy matters IV[electronic resource] :estimation for discretely observed Levy processes /

レコード種別:	言語・文字資料 (印刷物) : 単行資料
[NT 15000414] null:	519.2
タイトル / 著者:	Levy matters IV : estimation for discretely observed Levy processes // by Denis Belomestny ... [et al.].
その他の著者:	Belomestny, Denis.
出版された:	Cham : : Springer International Publishing :, 2015.
記述:	xv, 286 p. : : ill., digital ;; 24 cm.
含まれています:	Springer eBooks
主題:	Levy processes.
主題:	Mathematics.
主題:	Probability Theory and Stochastic Processes.
主題:	Statistics for Business/Economics/Mathematical Finance/Insurance.
主題:	Game Theory/Mathematical Methods.
国際標準図書番号 (ISBN) :	9783319123738 (electronic bk.)
国際標準図書番号 (ISBN) :	9783319123721 (paper)
[NT 15000228] null:	Estimation and calibration of Levy models via Fourier methods -- Adaptive Estimation for Levy processes -- Parametric estimation of Levy processes.
[NT 15000229] null:	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.
電子資源:	http://dx.doi.org/10.1007/978-3-319-12373-8

Levy matters IV[electronic resource] :estimation 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:

511896
Levy processes.

LC Class. No.: QA274.73

Dewey Class. No.: 519.2

Levy matters IV[electronic resource] :estimation for discretely observed Levy processes /
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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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