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Nonparametric estimation of a scalar diffusion model from discrete time data: a survey

Christian Gourieroux, Hung T. Nguyen () and Songsak Sriboonchitta ()
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Hung T. Nguyen: New Mexico State University
Songsak Sriboonchitta: Chiang Mai University

Annals of Operations Research, 2017, vol. 256, issue 2, 203-219

Abstract: Abstract 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.

Keywords: Diffusion model; Local time; Low frequency data; Nonlinear canonical analysis; Prediction operator (search for similar items in EconPapers)
Date: 2017
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Handle: RePEc:spr:annopr:v:256:y:2017:i:2:d:10.1007_s10479-016-2273-6