【作者】 宋鹏燕； 刘琼荪；

【Author】 SONG Peng-yan LIU Qiong-sun (College of Mathematics and Physics, Chongqing University, Chongqing 400030,China)

【机构】 重庆大学数理学院；

【摘要】 针对金融资产回报时间序列的尖峰厚尾性和波动集聚性,提出了基于AR(1)-GARCH(1,1)模型与幂律型分布相结合计算VaR的方法。用GARCH模型对时间序列建模刻画波动集聚性,用基于幂律型分布的扩展形式拟合GARCH模型的残差分布尾部,刻画回报时间序列的厚尾特征,二者结合更好地描述回报时序的动态波动现象。对上证综指进行实证分析,结果表明本文提出的方法比基于正态分布的GARCH模型和静态幂律尾法更精确。更多还原

【Abstract】 Aimed at the characteristics of peaks and fat tail and clustering fluctuation of financial asset return time series,an approach to evaluating VaR based on AR(1)-GARCH(1,1)model and power law distribution is de- veloped.Our approach combines GARCH model,which describes clustering fluctuation,and power law distribution for fitting the tail of residual,which describes the nature of fat tail,to depict phenomenon of dynamic volatility. Then an empirical analysis is done on Shangzheng index.The conclusion indicates that the approach is more precise than the static power law tail approach and the approach based on GARCH model,which is assumed as normal dis- tribution.更多还原