The Multivariate Garch Model and its Application to East Asian Financial Market Integration
The Multivariate Garch Model and its Application to East Asian Financial Market Integration
复制标题
多元Garch模型及其在东亚金融市场一体化中的应用
DOI：
10.1142/9789811202391_0123
复制
发表时间：
2020
期刊：
影响因子：
--
通讯作者：
and Miyakoshi T
中科院分区：
文献类型：
--
作者：
Tsukuda Y;Shimada J;and Miyakoshi T
我们简要回顾了多元 GARCH 模型与单变量 GARCH 模型的对比，并阐明了 Engel (2002) 引入的 DCC-GARCH 模型的统计视角。该模型巧妙地妥协了构建模型的两个相反的要求：足够灵活以捕捉实际观察到的数据过程的行为，以及足够简约以进行实践中的统计分析。然后，我们通过将 DCC-GARCH 应用于新兴东亚国家的债券和股票市场来说明其实际用途。除 DCC 外，DCC-GARCH 还可以利用动态方差分解（波动性溢出）来评估不同金融资产的联动性。本文的实证研究表明，债券市场一体化在 DCC 和波动性溢出方面仍然有限，而股票市场在区域和全球范围内都高度一体化。
We review briefly multivariate GARCH models in contrast with univariate GARCH models, and clarify the statistical perspective of the DCC-GARCH model introduced by Engel (2002). This model ingeniously compromises two contrary requirements for constructing a model: sufficiently flexible to catch the behaviors of actually observed data process, and sufficiently parsimonious for statistical analysis in practice. Then, we illustrate practical usefulness of the DCC-GARCH through its application to the bond and stock markets in the emerging East Asian countries. The DCC-GARCH can evaluate the comovements of different financial assets by use of dynamic variance decomposition (volatility spillover) in addition to the DCCs. Empirical investigation of this paper clarifies that the bond market integration is still limited in terms of both DCCs and volatility spillover, while the stock markets are highly integrated both regionally and globally.