Bootstrapping Stationary ARMA-GARCH Models
| Author/creator | Shimizu, Kenichi Author |
| Format | Electronic |
| Publication Info | Wiesbaden : Vieweg Verlag, Friedr, & Sohn Verlagsgesellschaft mbH Secaucus : Springer [Distributor] |
| Description | 148 p. ill 21.000 x 014.800 cm. |
| Supplemental Content | Full text available from Springer Books |
| Supplemental Content | Full text available from Springer Nature - Springer Mathematics and Statistics eBooks 2010 English International |
| Summary | Annotation Bootstrap technique is a useful tool for assessing uncertainty in statistical estimation and thus it is widely applied for risk management. Bootstrap is without doubt a promising technique, however, it is not applicable to all time series models. A wrong application could lead to a false decision to take too much risk. Kenichi Shimizu investigates the limit of the two standard bootstrap techniques, the residual and the wild bootstrap, when these are applied to the conditionally heteroscedastic models, such as the ARCH and GARCH models. The author shows that the wild bootstrap usually does not work well when one estimates conditional heteroscedasticity of Engle's ARCH or Bollerslev's GARCH models while the residual bootstrap works without problems. Simulation studies from the application of the proposed bootstrap methods are demonstrated together with the theoretical investigation. |
| Access restriction | Available only to authorized users. |
| Technical details | Mode of access: World Wide Web |
| Genre/form | Electronic books. |
| ISBN | 9783834809926 |
| ISBN | 3834809926 (Trade Paper) Active Record |
| Standard identifier# | 9783834809926 |
| Stock number | 3834809926 00713190 |
Availability
| Library | Location | Call Number | Status | Item Actions |
|---|---|---|---|---|
| Electronic Resources | ✔ Available |