Nonparametric estimation of a scalar diffusion model from discrete time data: a survey
© 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 ne...
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th-cmuir.6653943832-467462018-04-25T07:21:00Z Nonparametric estimation of a scalar diffusion model from discrete time data: a survey Christian Gourieroux Hung T. Nguyen Songsak Sriboonchitta Agricultural and Biological Sciences © 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. 2018-04-25T07:00:22Z 2018-04-25T07:00:22Z 2017-09-01 Journal 15729338 02545330 2-s2.0-84979266131 10.1007/s10479-016-2273-6 https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=84979266131&origin=inward http://cmuir.cmu.ac.th/jspui/handle/6653943832/46746 |
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Agricultural and Biological Sciences |
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Agricultural and Biological Sciences Christian Gourieroux Hung T. Nguyen Songsak Sriboonchitta Nonparametric estimation of a scalar diffusion model from discrete time data: a survey |
| description |
© 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. |
| format |
Journal |
| author |
Christian Gourieroux Hung T. Nguyen Songsak Sriboonchitta |
| author_facet |
Christian Gourieroux Hung T. Nguyen Songsak Sriboonchitta |
| author_sort |
Christian Gourieroux |
| title |
Nonparametric estimation of a scalar diffusion model from discrete time data: a survey |
| title_short |
Nonparametric estimation of a scalar diffusion model from discrete time data: a survey |
| title_full |
Nonparametric estimation of a scalar diffusion model from discrete time data: a survey |
| title_fullStr |
Nonparametric estimation of a scalar diffusion model from discrete time data: a survey |
| title_full_unstemmed |
Nonparametric estimation of a scalar diffusion model from discrete time data: a survey |
| title_sort |
nonparametric estimation of a scalar diffusion model from discrete time data: a survey |
| publishDate |
2018 |
| url |
https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=84979266131&origin=inward http://cmuir.cmu.ac.th/jspui/handle/6653943832/46746 |
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1681422931561807872 |