Modeling different kinds of spatial dependence in stock returns

被引：0
|
作者：
Matthias Arnold
Sebastian Stahlberg
Dominik Wied
机构：
[1] TU Dortmund,Fakultät Statistik
来源：
Empirical Economics | 2013年 / 44卷
关键词：
GMM estimation; Heteroscedasticity; Spatial dependence; Stock returns; Value at Risk; C13; C51; G12;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
The paper modifies previously suggested GMM approaches to spatial autoregression in stock returns. Our model incorporates global dependencies, dependencies inside industrial branches and local dependencies. As can be seen from Euro Stoxx 50 returns, this combination of spatial modeling and finance allows for superior risk forecasts in portfolio management.
引用
收藏
页码：761 / 774
页数：13
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