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On stationarity and β-mixing for ARMA-ACD model

Title
On stationarity and β-mixing for ARMA-ACD model
Authors
이미경
Issue Date
2003
Department/Major
대학원 통계학과
Publisher
이화여자대학교 대학원
Degree
Master
Abstract
Among the simplest and most widely-used models of stationary stochastic processes are the autoregressive moving-average or ARMA models. Engle and Russell(1995) developed a model for data that do not arrive in equal time intervals. This model is called the autoregressive conditional duration(ACD) model because the model formulation focuses on the intertemporally correlations of the duration. In this paper we will propose ARMA-ACD(p,q,r,s) models and give some evidences and proofs to show the new model is Markov geometrically ergodic, and if X_(0) is initialized from the invariant distribution, the X_(i) is strictly stationary and β mixing with exponential decay.
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일반대학원 > 통계학과 > Theses_Master
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