Non-parametric estimation of the coefficients of ergodic diffusion processes based on high-frequency data

Abstract : The content of this chapter is directly inspired by Comte, Genon-Catalot, and Rozenholc (2006; 2007). We consider non-parametric estimation of the drift and diffusion coefficients of a one-dimensional diffusion process. The main assumption on the diffusion model is that it is ergodic and geometrically β- mixing. The sample path is assumed to be discretely observed with a small regular sampling interval ∆. The estimation method that we develop is based on a penalized mean square approach. This point of view is fully investigated for regression models in Comte and Rozenholc (2002, 2004). We adapt it to discretized diffusion models.
Type de document :
Chapitre d'ouvrage
M. Kessler, A. Lindner, M. Sorensen. Statistical Methods for Stochastic Differential Equations, Chapman & Hall/CRC Monographs on Statistics & Applied Probability, pp.341-381, 2012, SemStat series
Liste complète des métadonnées


https://hal.archives-ouvertes.fr/hal-00748939
Contributeur : Yves Rozenholc <>
Soumis le : mardi 6 novembre 2012 - 12:36:43
Dernière modification le : mardi 11 octobre 2016 - 12:03:02
Document(s) archivé(s) le : jeudi 7 février 2013 - 03:45:04

Fichier

SemStatBook_359-399.pdf
Fichiers produits par l'(les) auteur(s)

Identifiants

  • HAL Id : hal-00748939, version 1

Collections

Citation

Fabienne Comte, Valentine Genon-Catalot, Yves Rozenholc. Non-parametric estimation of the coefficients of ergodic diffusion processes based on high-frequency data. M. Kessler, A. Lindner, M. Sorensen. Statistical Methods for Stochastic Differential Equations, Chapman & Hall/CRC Monographs on Statistics & Applied Probability, pp.341-381, 2012, SemStat series. <hal-00748939>

Partager

Métriques

Consultations de
la notice

252

Téléchargements du document

102