摘要
本文利用统计理论的优良点估计方法来估计金融市场风险的VaR和CVaR,既可避开现有方法中大量的模拟计算和参数估计等工作,又可提高估算精度。在资产-正态模型下,根据不同的风险估计要求,对金融资产的这两种风险分别提供了三种优良估计,即一致最小方差无偏估计,最佳线性次序统计量无偏估计,最佳线性次序统计量同变估计,并提供了实证分析。
In this paper, statistical method is used to improve the estimation of value-at-risk (VaR) and conditional value-at-risk (CVaR). These methods can avoid burdensome simulation calculation or parameters estimation and improve estimation precision. This paper discusses the optimal estimation of value-at-risk and conditional value-at-risk for assets under normal distribution and gives the uniformly minimum variance unbiased estimates (UMVUE), the best linear unbiased estimates (BLUE) and the best linear invariant estimates (BLIE) of VaR and CVaR based on order statistics. Furthermore, we show the practicability and validity of these methods through empirical analysis.
出处
《中国管理科学》
CSSCI
2006年第5期1-6,共6页
Chinese Journal of Management Science
基金
广西科学研究与技术开发资助项目(0385008)