Dynamic Conditional Correlation with Elliptical Distributions

M. Pelagatti
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引用次数: 15

Abstract

The Dynamic Conditional Correlation (DCC) model of Engle has made the estimation of multivariate GARCH models feasible for reasonably big vectors of securities’ returns. In the present paper we show how Engle’s multi-step estimation of the model can be easily extended to elliptical conditional distributions and apply different leptokurtic DCC models to twenty shares listed at the Milan Stock Exchange.
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椭圆分布的动态条件相关
恩格尔的动态条件相关(DCC)模型使得多元GARCH模型对较大的证券收益向量的估计成为可能。在本文中,我们展示了如何将Engle模型的多步估计很容易地推广到椭圆条件分布,并将不同的细峰DCC模型应用于米兰证券交易所上市的20只股票。
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