Xie, Yingfu
- Department of Forest Economics, Swedish University of Agricultural Sciences
Research article2003
Quasi-Maximum Likelihood Estimators in GARCH(1,2) Model: Asymptotics and Applications
Yingfu Xie, Yu Jun
Abstract
In this paper, we investigate the asymptotic properties of the quasi-maximum likelihood estimator (quasi-MLE) for GARCH(1,2) model. Consistency of the global quasi-MLE and asymptotic normality of the local quasi-MLE are obtained, which extend the results in Lee and Hansen (1994) for GARCH(1,1). Two sets of financial data, stock returns in Standard and Poor's 500 Index and Shanghai Stock Exchange Index, are analyzed as applications. It is shown that more complicated models than GARCH(1,1) for describing the variance process are needed for daily data
Keywords
GARCH; quasi-maximum likehood estimator; consistency; asymptotic normality; S&P 500; SEE
Published in
Research report (Centre of Biostochastics)
2003, Volume: 2003, number: 5, pages: 1-28
Publisher: SLU
Yu, Jun
- Department of Forest Economics, Swedish University of Agricultural Sciences
- Department of Forest Economics, Swedish University of Agricultural Sciences
SLU Authors
Permanent link to this page (URI)
https://res.slu.se/id/publ/134