EconPapers    
Economics at your fingertips  
 

On Diagnostic Checking of Vector ARMA-GARCH Models with Gaussian and Student-t Innovations

Yongning Wang and Ruey S. Tsay
Additional contact information
Yongning Wang: Booth School of Business, University of Chicago, 5807 South Woodlawn Avenue, Chicago,IL 60637, USA
Ruey S. Tsay: Booth School of Business, University of Chicago, 5807 South Woodlawn Avenue, Chicago,IL 60637, USA

Econometrics, 2013, vol. 1, issue 1, 1-31

Abstract: This paper focuses on the diagnostic checking of vector ARMA (VARMA) models with multivariate GARCH errors. For a fitted VARMA-GARCH model with Gaussian or Student-t innovations, we derive the asymptotic distributions of autocorrelation matrices of the cross-product vector of standardized residuals. This is different from the traditional approach that employs only the squared series of standardized residuals. We then study two portmanteau statistics, called Q1(M) and Q2(M), for model checking. A residual-based bootstrap method is provided and demonstrated as an effective way to approximate the diagnostic checking statistics. Simulations are used to compare the performance of the proposed statistics with other methods available in the literature. In addition, we also investigate the effect of GARCH shocks on checking a fitted VARMA model. Empirical sizes and powers of the proposed statistics are investigated and the results suggest a procedure of using jointly Q1(M) and Q2(M) in diagnostic checking. The bivariate time series of FTSE 100 and DAX index returns is used to illustrate the performance of the proposed portmanteau statistics. The results show that it is important to consider the cross-product series of standardized residuals and GARCH effects in model checking.

Keywords: Vector autoregressive moving-average process; multivariate GARCH model; asymptotic distribution; portmanteau statistic; model checking; heavy tail; multivariate time series; bootstrap (search for similar items in EconPapers)
JEL-codes: B23 C C00 C01 C1 C2 C3 C4 C5 C8 (search for similar items in EconPapers)
Date: 2013
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

Downloads: (external link)
https://www.mdpi.com/2225-1146/1/1/1/pdf (application/pdf)
https://www.mdpi.com/2225-1146/1/1/1/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jecnmx:v:1:y:2013:i:1:p:1-31:d:24773

Access Statistics for this article

Econometrics is currently edited by Ms. Jasmine Liu

More articles in Econometrics from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().

 
Page updated 2025-03-19
Handle: RePEc:gam:jecnmx:v:1:y:2013:i:1:p:1-31:d:24773