Premium
A mixed portmanteau test for ARMA‐GARCH models by the quasi‐maximum exponential likelihood estimation approach
Author(s) -
Zhu Ke.
Publication year - 2013
Publication title -
journal of time series analysis
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.576
H-Index - 54
eISSN - 1467-9892
pISSN - 0143-9782
DOI - 10.1111/jtsa.12007
Subject(s) - mathematics , autoregressive conditional heteroskedasticity , autocorrelation , statistics , exponential function , residual , asymptotic distribution , autoregressive–moving average model , exponential distribution , econometrics , autoregressive model , volatility (finance) , algorithm , mathematical analysis , estimator
This paper investigates the joint limiting distribution of the residual autocorrelation functions and the absolute residual autocorrelation functions of ARMA‐GARCH models. 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.