摘要
为更深刻地揭示沪深股指收益率特征,本文提出两成分混合广义正态分布及其退化分布、非对称广义正态分布及其退化分布等8种分布,对上证综指(SSEC)和深证成指(SZCZ)日收益率数据进行拟合对比分析。通过拟合评价和VaR度量发现:对于上证综指,用非对称广义正态分布更好地拟合日收益率数据的尖峰厚尾带偏特征;对于深证成指,用两成分混合广义正态分布更好地拟合日收益率数据的尖峰厚尾带偏特征。在进行沪深股指波动率预测、资产定价和风险度量时,建议选择非对称广义正态分布和两成分混合广义正态分布进行对比分析,进一步提高其准确性。
In order to more deeply reveal the characteristics of Shanghai and Shenzhen stock index returns,this paper proposes eight distributions,including two-component mixed generalized normal distribution and its degenerate distribution,asymmetric generalized normal distribution and its degenerate distribution,and conducts fitting and comparative analysis on the daily yield data of SSEC and SZCZ.Through fitting evaluation and VaR measurement,it found that for the Shanghai Composite Index,the asymmetric generalized normal distribution is better used to fit the peak and thick tail bias characteristics of daily yield data;For the Shenzhen Composite Index,the two-component mixed generalized normal distribution used to better fit the peak and thick tail bias characteristics of daily yield data.When forecasting Shanghai and Shenzhen stock index volatility,asset pricing and risk measurement,it recommended to select asymmetric generalized normal distribution and two-component mixed generalized normal distribution for comparative analysis to further improve its accuracy.
出处
《价格理论与实践》
北大核心
2023年第1期92-95,198,共5页
Price:Theory & Practice
基金
广东省哲学社会科学“十三五”规划学科共建项目“基于非对称广义正态分布理论的金融数据建模研究”(编号:GD20XYJ19)
关键词
沪深股市
股指收益率
上证综指
深证成指
Shanghai and Shenzhen stock markets
stock index yield
Shanghai Composite Index
Shenzhen Composite Index
