Li, Dong and Ling, Shiqing and Zhu, Ke (2016): ZDGARCH model: a new way to study heteroscedasticity.

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Abstract
This paper proposes a firstorder zerodrift GARCH (ZDGARCH(1, 1)) model to study conditional heteroscedasticity and heteroscedasticity together. Unlike the classical GARCH model, ZDGARCH(1, 1) model is always nonstationary regardless of the sign of the Lyapunov exponent $\gamma_{0}$ , but interestingly when $\gamma_{0}$ = 0, it is stable with its sample path oscillating randomly between zero and infinity over time. Furthermore, this paper studies the generalized quasimaximum likelihood estimator (GQMLE) of ZDGARCH(1, 1) model, and establishes its strong consistency and asymptotic normality. Based on the GQMLE, an estimator for $\gamma_{0}$, a test for stability, and a portmanteau test for model checking are all constructed. Simulation studies are carried out to assess the finite sample performance of the proposed estimators and tests. Applications demonstrate that a stable ZDGARCH(1, 1) model is more appropriate to capture heteroscedasticity than a nonstationary GARCH(1, 1) model, which suffers from an inconsistent QMLE of the drift term
Item Type:  MPRA Paper 

Original Title:  ZDGARCH model: a new way to study heteroscedasticity 
English Title:  ZDGARCH model: a new way to study heteroscedasticity 
Language:  English 
Keywords:  Conditional heteroscedasticity; GARCH model; Generalized quasimaximum likelihood estimator; Heteroscedasticity; Portmanteau test; Stability test; Top Lyapunov exponent; Zerodrift GARCH model. 
Subjects:  C  Mathematical and Quantitative Methods > C0  General C  Mathematical and Quantitative Methods > C0  General > C01  Econometrics C  Mathematical and Quantitative Methods > C5  Econometric Modeling C  Mathematical and Quantitative Methods > C5  Econometric Modeling > C51  Model Construction and Estimation 
Item ID:  68621 
Depositing User:  Dr. Ke Zhu 
Date Deposited:  02 Jan 2016 11:15 
Last Modified:  28 Sep 2019 08:56 
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URI:  https://mpra.ub.unimuenchen.de/id/eprint/68621 