Proximity-Structured Multivariate Volatility Models
Proximity-Structured Multivariate Volatility Models
复制标题
邻近结构多元波动率模型
DOI：
10.1080/07474938.2013.807102
复制
发表时间：
2012
期刊：
影响因子：
--
通讯作者：
P. Paruolo
中科院分区：
文献类型：
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作者：
M. Caporin;P. Paruolo
在许多多变量波动模型中，参数的增加速度快于横截面维数的增加速度，因此产生了维数灾难问题。本文讨论了基于经济邻近性的权矩阵的结构化参数的描述和识别。结果表明，结构化规格说明可以减轻甚至解决维数灾难问题。分析了结构化指标的辨识与估计，给出了辨识的秩和阶条件，讨论了权矩阵的确定。几个结构化的规格比较以及与替代品的建模条件协方差的六个回报从纽约证券交易所。
In many multivariate volatility models, the number of parameters increases faster than the cross-section dimension, hence creating a curse of dimensionality problem. This paper discusses specification and identification of structured parameterizations based on weight matrices induced by economic proximity. It is shown that structured specifications can mitigate or even solve the curse of dimensionality problem. Identification and estimation of structured specifications are analyzed, rank and order conditions for identification are given and the specification of weight matrices is discussed. Several structured specifications compare well with alternatives in modelling conditional covariances of six returns from the New York Stock Exchange.