然而多元时间序列的数据结构比一元时间序列更复杂，现有的理论和方法仍不够完善。
However, there are a few on multivariate time series mining, since the data structure of multivariate time series is more complex than that of univariate time series.
在这篇文章里，笔者主要关注当同时考察多支金融时间序列的波动时，多元GARCH模型相比于一元GARCH模型而言，对相关系数和波动性的更好的描述。
In this article, the author concerned with a better description of the volatility and correlations under multivariate GARCH model compared with univariate GARCH model.
笔者首先讨论了在金融时间序列的考察中从一元GARCH模型扩展到多元GARCH模型的必要性。分析了多元GARCH模型在金融建模中的重要作用。
First of all, the author discusses the extension from univariate GARCH to multivariate GARCH model and the important role of the MGARCH model in the modern financial research.
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