| Full text | |
| Author(s): |
Trucios, Carlos
;
Hotta, Luiz K.
;
Ruiz, Esther
Total Authors: 3
|
| Document type: | Journal article |
| Source: | JOURNAL OF STATISTICAL COMPUTATION AND SIMULATION; v. 87, n. 16, p. 3152-3174, 2017. |
| Web of Science Citations: | 3 |
| Abstract | |
Bootstrap procedures are useful to obtain forecast densities for both returns and volatilities in the context of generalized autoregressive conditional heteroscedasticity models. In this paper, we analyse the effect of additive outliers on the finite sample properties of these bootstrap densities and show that, when obtained using maximum likelihood estimates of the parameters and standard filters for the volatilities, they are badly affected with dramatic consequences on the estimation of Value-at-Risk. We propose constructing bootstrap densities for returns and volatilities using a robust parameter estimator based on variance targeting implemented together with an adequate modification of the volatility filter. We show that the performance of the proposed procedure is adequate when compared with available robust alternatives. The results are illustrated with both simulated and real data. (AU) | |
| FAPESP's process: | 13/00506-1 - Time series, wavelets and functional data analysis |
| Grantee: | Pedro Alberto Morettin |
| Support Opportunities: | Research Projects - Thematic Grants |
| FAPESP's process: | 13/23524-5 - Bootstrap prediction intervals to forecast portfolio value-at-risk |
| Grantee: | Carlos Cesar Trucios Maza |
| Support Opportunities: | Scholarships abroad - Research Internship - Doctorate |
| FAPESP's process: | 12/09596-0 - Bootstrap prediction in univariate and multivariate volatility models |
| Grantee: | Carlos Cesar Trucios Maza |
| Support Opportunities: | Scholarships in Brazil - Doctorate |