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Analysis of the Dependence among Inland, Hong Kong and London Stock Markets When Hong Kong Returned to China

机译:香港回归中国后内地,香港和伦敦股市之间的依存关系分析

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A common approach to the estimation of copula-based models is the method of inference functions for margins (IFM). However, IFM is subject to small-sample bias. This paper proposes to estimate Copula-MGARCH models by applying maximization by parts (MBP), a multi-step optimization algorithm. The results show that, although the inland stock markets and the Hong Kong stock markets, London stock markets and the Hong Kong stock markets as well as the inland stock markets and the London stock markets, have weak correlations, but since reunification, the three correlation parameters are all improved, and the correlation between inland and Hong Kong stock markets has increased remarkably. In addition, as another conclusion of this paper, IFM overestimates the conditional covariance matrices compared with MBP. Meanwhile, MBP estimates have much better performance.
机译:估计基于系动词的模型的常用方法是边际推理函数(IFM)的方法。但是,IFM会受到小样本偏差的影响。本文提出通过应用零件最大化(MBP)(一种多步优化算法)来估计Copula-MGARCH模型。结果表明,尽管内陆股市和香港股市,伦敦股市和香港股市以及内陆股市和伦敦股市之间的相关性较弱,但自统一以来,这三个相关性各项参数均得到改善,内地与香港股市之间的相关性显着提高。另外,作为本文的另一个结论,IFM与MBP相比高估了条件协方差矩阵。同时,MBP估计具有更好的性能。

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