|
EconStor >
Humboldt-Universität Berlin >
Sonderforschungsbereich 649: Ökonomisches Risiko, Humboldt-Universität Berlin >
SFB 649 Discussion Papers, HU Berlin >
Please use this identifier to cite or link to this item:
http://hdl.handle.net/10419/25116
|
| | |
| Title: | | Varying coefficient GARCH versus local constant volatility modeling: comparison of the predictive power  |
| Authors: | | Polzehl, Jörg Spokoiny, Vladimir |
| Issue Date: | | 2006 |
| Series/Report no.: | | SFB 649 discussion paper 2006,033 |
| Abstract: | | GARCH models are widely used in financial econometrics. However, we show by mean of a simple simulation example that the GARCH approach may lead to a serious model misspecification if the assumption of stationarity is violated. In particular, the well known integrated GARCH effect can be explained by nonstationarity of the time series. We then introduce a more general class of GARCH models with time varying coefficients and present an adaptive procedure which can estimate the GARCH coefficients as a function of time. We also discuss a simpler semiparametric model in which the ¯ - parameter is fixed. Finally we compare the performance of the parametric, time varying nonparametric and semiparametric GARCH(1,1) models and the locally constant model from Polzehl and Spokoiny (2002) by means of simulated and real data sets using different forecasting criteria. Our results indicate that the simple locally constant model outperforms the other models in almost all cases. The GARCH(1,1) model also demonstrates a relatively good forecasting performance as far as the short term forecasting horizon is considered. However, its application to long term forecasting seems questionable because of possible misspecification of the model parameters. |
| JEL: | | C14 C22 C53 |
| Document Type: | | Working Paper |
| Appears in Collections: | | SFB 649 Discussion Papers, HU Berlin
|
| Files in This Item:
| |
|
| No. of Downloads:
| |
| last Month |
last 3 Month |
total |
|
|
|
|
|
| |
| | |
Download bibliographical data as:
BibTeX
|
| |
Share on:http://hdl.handle.net/10419/25116
|
Items in EconStor are protected by copyright, with all rights reserved, unless otherwise indicated.
|