Please use this identifier to cite or link to this item: http://cmuir.cmu.ac.th/jspui/handle/6653943832/57176
Title: Nonparametric estimation of a scalar diffusion model from discrete time data: a survey
Authors: Christian Gourieroux
Hung T. Nguyen
Songsak Sriboonchitta
Keywords: Decision Sciences
Issue Date: 1-Sep-2017
Abstract: © 2016, Springer Science+Business Media New York. In view of rapid developments on nonparametric estimation of the drift and volatility functions in scalar diffusion models in financial econometrics, from discrete-time observations, we provide, in this paper, a survey of its state-of-the-art with new insights into current practices, as well as elaborating on our own recent contributions. In particular, in presenting the main principles of estimation for both stationary and nonstationary cases, we show the possibility to estimate nonparametrically the drift and volatility functions without distinguishing these two frameworks.
URI: https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=84979266131&origin=inward
http://cmuir.cmu.ac.th/jspui/handle/6653943832/57176
ISSN: 15729338
02545330
Appears in Collections:CMUL: Journal Articles

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