A mixed portmanteau test for ARMA-GARCH model by the quasi-maximum exponential likelihood estimation approach
AbstractThis paper investigates the joint limiting distribution of the residual autocorrelation functions and the absolute residual autocorrelation functions of ARMA-GARCH model. This leads a mixed portmanteau test for diagnostic checking of the ARMA-GARCH model fitted by using the quasi-maximum exponential likelihood estimation approach in Zhu and Ling (2011). Simulation studies are carried out to examine our asymptotic theory, and assess the performance of this mixed test and other two portmanteau tests in Li and Li (2008). A real example is given.
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Bibliographic InfoPaper provided by University Library of Munich, Germany in its series MPRA Paper with number 40382.
Date of creation: 31 Jul 2012
Date of revision:
ARMA-GARCH model; LAD estimator; mixed portmanteau test; model diagnostics; quasi-maximum exponential likelihood estimator;
Other versions of this item:
- Ke. Zhu, 2013. "A mixed portmanteau test for ARMA-GARCH models by the quasi-maximum exponential likelihood estimation approach," Journal of Time Series Analysis, Wiley Blackwell, vol. 34(2), pages 230-237, 03.
- C10 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - General
- C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
This paper has been announced in the following NEP Reports:
- NEP-ALL-2012-08-23 (All new papers)
- NEP-ECM-2012-08-23 (Econometrics)
- NEP-ETS-2012-08-23 (Econometric Time Series)
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