期刊
JOURNAL OF BUSINESS & ECONOMIC STATISTICS
卷 20, 期 3, 页码 339-350出版社
AMER STATISTICAL ASSOC
DOI: 10.1198/073500102288618487
关键词
ARCK; correlation; GARCH; multivariate GARCH
Time varying correlations are often estimated with multivariate generalized autoregressive conditional heteroskedasticity (GARCH) models that are linear in squares and cross products of the data. A new class of multivariate models called dynamic conditional correlation models is proposed. These have the flexibility of univariate GARCH models coupled with parsimonious parametric models for the correlations. They are not linear but can often be estimated very simply with univariate or two-step methods based on the likelihood function. It is shown that they perform well in a variety of situations and provide sensible empirical results.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据