GMM estimation;
Heteroscedasticity;
Spatial dependence;
Stock returns;
Value at Risk;
D O I:
10.1007/s00181-011-0528-2
中图分类号:
F [经济];
学科分类号:
02 ;
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.
机构:S China Univ Technol, Sch Business Adm, Guangzhou 510641, Guangdong, Peoples R China
Xu, Weidong
Wu, Chongfeng
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机构:
Shanghai Jiao Tong Univ, Financial Engn Res Ctr, Shanghai 200240, Peoples R ChinaS China Univ Technol, Sch Business Adm, Guangzhou 510641, Guangdong, Peoples R China
Wu, Chongfeng
Dong, Yucheng
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机构:
Xi An Jiao Tong Univ, Sch Management, Xian 710049, Shannxi, Peoples R ChinaS China Univ Technol, Sch Business Adm, Guangzhou 510641, Guangdong, Peoples R China
Dong, Yucheng
Xiao, Weilin
论文数: 0引用数: 0
h-index: 0
机构:
S China Univ Technol, Sch Business Adm, Guangzhou 510641, Guangdong, Peoples R ChinaS China Univ Technol, Sch Business Adm, Guangzhou 510641, Guangdong, Peoples R China