摘要
金融数据呈现的厚尾性已达成共识。本文首先基于指数回归模型提出了一种厚尾分布的极值分位数估计方法,得到了在险风险值的估计公式。然后得到了上海上证指数、国债指数和企业债券指数的在险风险值的估计值,比较了他们的极值风险.
It is well known that finance data tends to heavy-tailed.On the basis of an exponential regression model,this paper proposed an extreme quantile estimator method of heavy-tailed distribution and obtained the estimation formula of value-at-risk(VaR).Then,the estimations of value-at-risk(VaR) of the synthesized index of Shanghai,treasury and corporate bond indexes of China were obtained,and their extremal risk was compared.
出处
《经济数学》
北大核心
2010年第4期15-21,共7页
Journal of Quantitative Economics
基金
国家自然科学基金资助项目(10871064)
湖南省普通高校<计算与随机数学及其应用>重点实验室,开放基金资助项目(09K026)
湖南师范大学青年基金资助项目(71001)