摘要
绝大多数风险价值的计算方法都将正态分布作为最基本的假设前提 ,然而大量的实证研究表明 ,金融回报序列往往呈现出明显的尖峰厚尾特性 ,这使得在正态分布假设下所计算出的风险价值常常会低估实际风险。其原因在于正态分布假设不能很好的体现回报分布的尾部特征。文章尝试引入 POT( Peak OverThreshold)模型来克服正态分布的这一缺陷 。
Most methods of VaR calculation are based on the hypothesis of normal distribution, but many empirical studies indicate that the real distribution of the percentage price change is not normal distribution for it has fatter tails and a thinner waist. So the VaR on the basis of normal distribution often leads to underestimation of the real risk. The reason lies in the hypothesis which can not exhibit the tail's character of the real loss. In this paper a POT model is applied to conquer the shortcoming of normal distribution hypothesis in order to increase the accuracy of VaR estimation.
出处
《华中科技大学学报（社会科学版）》
2003年第5期97-100,共4页
Journal of Huazhong University of Science and Technology(Social Science Edition)
