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이외숙 한국데이터정보과학회 2011 한국데이터정보과학회지 Vol.22 No.2
We consider an asymmetric power transformed threshold GARCH(1.1) process and find sufficient conditions for the existence of a strictly stationary solution, geometric ergodicity and β-mixing property. Moments conditions are given. Box-Cox transformed threshold GARCH(1.1) process is also considered as a special case.
Sufficient Conditions for Stationarity of Smooth Transition ARMA/GARCH Models
이외숙 한국데이터정보과학회 2007 한국데이터정보과학회지 Vol.18 No.1
Nonlinear asymmetric time series models have the growing interest in econometrics and finance. Threshold model is one of the successful asymmetric model. We consider a smooth transition ARMA model which converges a.s. to a threshold ARMA model and show that the smooth transition ARMA model admits a stationary measure, provided a suitable condition on the coefficients of the autoregressive parts of the different regimes is satisfied. Stationarity of a smooth transition GARCH model is also obtained.
Long Memory and Covariance Stationary of Asymmetric Power FIGARCH Model
이외숙,김미정 한국데이터정보과학회 2006 한국데이터정보과학회지 Vol.17 No.3
In this paper, we study an asymmetric power fractionally integrated GARCH model and find a region on which the process is stationary ergodic and has long memory property.
A continuous time asymmetric power GARCH process driven by a Lévy process
이외숙 한국데이터정보과학회 2010 한국데이터정보과학회지 Vol.21 No.6
A continuous time asymmetric power GARCH(1,1) model is suggested, based on a single background driving Lévy process. The stochastic dierential equation for the given process is derived and the strict stationarity and kth order moment conditions are examined.
Functional central limit theorems for augmented GARCH(p, q) and FIGARCH processes
이외숙 한국통계학회 2014 Journal of the Korean Statistical Society Vol.43 No.3
In this paper, we study the functional central limit theorem(FCLT) for the augmentedGARCH process introduced by Duan (1997). We prove under proper moment assumptionsthat the process is geometrically L2-NED and then the FCLT holds. The fractional FCLT forFIGARCH processes is also considered. We examine the FCLT for the APGARCH, EGARCHand HYGARCH models as examples.
Covariance stationary GARCH-family models with long memory property
이외숙,H.M. Kim 한국통계학회 2008 Journal of the Korean Statistical Society Vol.37 No.1
We propose simple models which extend GARCH model and nd regions of coefcients on which the given process isnonnegative covariance stationary and has long memory property.
On Strict Stationarity of Nonlinear ARMA Processeswith Nonlinear GARCH Innovations
이외숙 한국통계학회 2007 Journal of the Korean Statistical Society Vol.36 No.3
We consider a nonlinear autoregressive moving average model with non-linear GARCH errors, and nd sucient conditions for the existence of astrictly stationary solution of three related time series equations. We alsoconsider a geometric ergodicity and functional central limit theorem for anonlinear autoregressive model with nonlinear ARCH errors. The givenmodel includes broad classes of nonlinear models. New results are obtained,and known results are shown to emerge as special cases.
이외숙,김경화 한국데이터정보과학회 2007 한국데이터정보과학회지 Vol.18 No.1
Nonlinear ARMA model is considered and easy-to-check sufficient condition for strict stationarity of without some irreducibility or continuity assumption is given. Threshold ARMA(p, q) and momentum threshold ARMA(p, q) models are examined as special cases.