On buffered threshold GARCH models

Pak Hang LO, Wai Keung LI, Philip L. H. YU, Guodong LI

Research output: Contribution to journalArticle

2 Citations (Scopus)

Abstract

This paper proposes a conditional heteroscedastic model with a new piecewise linear structure such that the regime-switching mechanism has a buffer zone where regime-switching is delayed. Gaussian quasi-maximum likelihood estimation (QMLE) is considered, and its asymptotic behaviors, including strong consistency and the asymptotic distribution, are derived. Its finite sample performance is evaluated by Monte Carlo simulation experiments, and an empirical example is reported to give further support to the new model. Copyright © 2016 Institute of Statistical Science.
Original languageEnglish
Pages (from-to)1555-1567
JournalStatistica Sinica
Volume26
DOIs
Publication statusPublished - Oct 2016

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Regime Switching
Threshold Model
GARCH Model
Quasi-maximum Likelihood
Heteroscedastic Model
Conditional Model
Strong Consistency
Monte Carlo Experiment
Maximum Likelihood Estimation
Piecewise Linear
Asymptotic distribution
Simulation Experiment
Buffer
Monte Carlo Simulation
Asymptotic Behavior
Regime switching
GARCH model
Model
Conditional model
Quasi-maximum likelihood estimation

Citation

Lo, P. H., Li, W. K., Yu, P. L. H., & Li, G. (2016). On buffered threshold GARCH models. Statistica Sinica, 26, 1555-1567. doi: 10.5705/ss.2014.098t

Keywords

  • Buffered threshold model
  • GARCH model
  • QMLE
  • Threshold model