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首页> 外文期刊>Annals of the Institute of Statistical Mathematics >JOINT MODELING OF COINTEGRATION AND CONDITIONAL HETEROSCEDASTICITY WITH APPLICATIONS
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JOINT MODELING OF COINTEGRATION AND CONDITIONAL HETEROSCEDASTICITY WITH APPLICATIONS

机译:协整和条件异方差的联合建模及其应用

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摘要

A cointegrated vector AR-GARCH time series model is introduced. Least squares estimator, full rank maximum likelihood estimator (MLE), and reduced rank MLE of the model are presented. Monte Carlo experiments are conducted to illustrate the finite sample properties of the estimators. Its applicability is then demonstrated with the modeling of international stock indices and exchange rates. The model leads to reasonable financial interpretations.
机译:介绍了一种协整矢量AR-GARCH时间序列模型。提出了模型的最小二乘估计器,满秩最大似然估计器(MLE)和降阶MLE。进行了蒙特卡洛实验,以说明估计量的有限样本属性。然后,通过对国际股票指数和汇率进行建模来证明其适用性。该模型导致合理的财务解释。

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