基于改进的RiskMetrics模型的股票市场风险度量  被引量:2

Stock market risk measurement based on improved RiskMetrics model

在线阅读下载全文

作  者:周东海 陈滨霞 蒋远营[1] ZHOU Dong-hai;CHEN Bin-xia;JIANG Yuan-ying(College of Science,Guilin University of Technology,Guilin 541006,China)

机构地区:[1]桂林理工大学理学院,广西桂林541006

出  处:《桂林理工大学学报》2021年第4期926-934,共9页Journal of Guilin University of Technology

基  金:国家自然科学基金项目(71963008);广西自然科学基金项目(2018GXNSFAA294131)。

摘  要:对RiskMetrics模型两个假设做出改进,并运用改进的RiskMetrics模型对2007年1月至2018年9月的国内外股票指数日收盘价序列进行建模,实证结果表明:改进的RiskMetrics模型可以更加精准刻画三类股指序列的在险价值。美国股市对利空消息的反应非常剧烈,沪深股市与香港股市之间具有趋同性,但两者对新息冲击的反应有所不同,沪深股市对利空消息与利好消息的反应区别不明显,而香港股市对利空消息的反应明显强于利好消息。另外,三类指数的收益率序列均呈“尖峰厚尾”特性;股票价格波动对冲击的反应速度由高到低依次是美国股市、香港股市、内地股市,而对冲击的持久性由强至弱的排序则恰恰相反。In this paper,two assumptions of RiskMetrics model are improved.The improved RiskMetrics model was used to model the daily closing price series of domestic and foreign stock index from January 2007 to September 2018.The empirical results show that the improved RiskMetrics model can accurately depict the risk value of three kinds of stock index sequences.The reaction of the US stock market to the bad news is very intense.There is a convergence between the Shanghai and Shenzhen stock markets and the Hong Kong stock market,but the reactions of the two to the new interest shock are different.The Shanghai and Shenzhen stock markets have no obvious difference in response to the bad news and the good news,while the reaction of the Hong Kong stock market to the bad news is obviously stronger than to the good news.In addition,the yield series of the three indexes are“leptokurtosis and fat-tail”.The response speed of stock price volatility to shock is the US stock market,the Hong Kong stock market and the mainland stock market,while the order of the persistence of the shock is the opposite.

关 键 词:股指收盘价 在险价值 尖峰厚尾 杠杆效应 

分 类 号:F224[经济管理—国民经济] F830.91

 

参考文献:

正在载入数据...

 

二级参考文献:

正在载入数据...

 

耦合文献:

正在载入数据...

 

引证文献:

正在载入数据...

 

二级引证文献:

正在载入数据...

 

同被引文献:

正在载入数据...

 

相关期刊文献:

正在载入数据...

相关的主题
相关的作者对象
相关的机构对象