Combining Nonparametric and Optimal Linear Time Series Predictions
We introduce a semiparametric procedure for more efficient prediction of a strictly stationaryprocess admitting an ARMA representation. The procedure is based on the estimation of the ARMArepresentation, followed by a nonparametric regression where the ARMA residuals are used as explanatoryvariables. Compared to standard nonparametric regression methods, the number of explanatory variablescan be reduced because our approach exploits the linear dependence of the process. We establish consistencyand asymptotic normality results. A Monte Carlo study and an empirical application on stockindices suggest that significant gains can be achieved with our approach.
|Date of creation:||2009|
|Date of revision:|
|Contact details of provider:|| Postal: 15 Boulevard Gabriel Peri 92245 Malakoff Cedex|
Phone: 01 41 17 60 81
Web page: http://www.crest.fr
More information through EDIRC
References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Enno Mammen, .
"Comparing nonparametric versus parametric regression fits,"
Statistic und Oekonometrie
9205, Humboldt Universitaet Berlin.
- Hardle, W. & Mammen, E., 1990. "Comparing nonparametric versus parametric regression fits," CORE Discussion Papers 1990065, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
- Oliver LINTON, .
"Applied nonparametric methods,"
Statistic und Oekonometrie
9312, Humboldt Universitaet Berlin.
- Drost, F.C. & Klaasens, C.A.J. & Werker, B.J.M., 1994.
"Adaptive Estimation in Time Series Models,"
9488, Tilburg - Center for Economic Research.
- Ke-Li Xu & Peter C.B. Phillips, 2006.
"Adaptive Estimation of Autoregressive Models with Time-Varying Variances,"
Cowles Foundation Discussion Papers
1585, Cowles Foundation for Research in Economics, Yale University.
- Xu, Ke-Li & Phillips, Peter C.B., 2008. "Adaptive estimation of autoregressive models with time-varying variances," Journal of Econometrics, Elsevier, vol. 142(1), pages 265-280, January.
- Ke-Li Xu & Peter C.B. Phillips, 2006. "Adaptive Estimation of Autoregressive Models with Time-Varying Variances," Cowles Foundation Discussion Papers 1585R, Cowles Foundation for Research in Economics, Yale University, revised Nov 2006.
- Schennach, Susanne M., 2004. "Nonparametric Regression In The Presence Of Measurement Error," Econometric Theory, Cambridge University Press, vol. 20(06), pages 1046-1093, December.
- Härdle, W.K., 1992.
"Applied Nonparametric Methods,"
1992-6, Tilburg University, Center for Economic Research.
- HÄRDLE, Wolfgang, 1992. "Applied nonparametric methods," CORE Discussion Papers 1992003, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
- Wolfgang Hardle & Oliver Linton, 1994. "Applied Nonparametric Methods," Cowles Foundation Discussion Papers 1069, Cowles Foundation for Research in Economics, Yale University.
- Hardle, W., 1992. "Applied Nonparametric Methods," Papers 9206, Tilburg - Center for Economic Research.
- Hardle, W., 1992. "Applied Nonparametric Methods," Papers 9204, Catholique de Louvain - Institut de statistique.
- Carrasco, Marine & Chen, Xiaohong, 2002. "Mixing And Moment Properties Of Various Garch And Stochastic Volatility Models," Econometric Theory, Cambridge University Press, vol. 18(01), pages 17-39, February.
- Fan, Yanqin & Ullah, Aman, 1999. "Asymptotic Normality of a Combined Regression Estimator," Journal of Multivariate Analysis, Elsevier, vol. 71(2), pages 191-240, November.
- Anton Schick & Wolfgang Wefelmeyer, 2004. "Root "n" consistent and optimal density estimators for moving average processes," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 31(1), pages 63-78.
- Hall, Peter & Yatchew, Adonis, 2005. "Unified approach to testing functional hypotheses in semiparametric contexts," Journal of Econometrics, Elsevier, vol. 127(2), pages 225-252, August.
- Liebscher E., 2001. "Estimation Of The Density And The Regression Function Under Mixing Conditions," Statistics & Risk Modeling, De Gruyter, vol. 19(1), pages 9-26, January.
- Gao, Jiti & Tong, Howell & Wolff, Rodney, 2002. "Model Specification Tests in Nonparametric Stochastic Regression Models," Journal of Multivariate Analysis, Elsevier, vol. 83(2), pages 324-359, November.
When requesting a correction, please mention this item's handle: RePEc:crs:wpaper:2009-18. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Florian Sallaberry)
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If references are entirely missing, you can add them using this form.
If the full references list an item that is present in RePEc, but the system did not link to it, you can help with this form.
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your profile, as there may be some citations waiting for confirmation.
Please note that corrections may take a couple of weeks to filter through the various RePEc services.