首页 | 本学科首页   官方微博 | 高级检索  
     检索      


Density approximations and VaR computation for compound Poisson-lognormal distributions
Authors:M Bee
Institution:Department of Economics and Management, University of Trento, Trento, Italy
Abstract:Parametric approximations of the compound Poisson-lognormal distribution are developed and used to compute Value-at-Risk (VaR). As guidelines for finding an approximation, the skewness–kurtosis space and the tail behavior are considered. The Generalized Beta distribution of the second kind (GB2) and a mixture of lognormals are found to provide a good fit. In certain cases, the GB2 can be estimated by moment-matching, thus providing a simulation-free procedure for VaR computation. For confidence levels larger than 99%, extreme value theory approaches are developed. According to extensive Monte Carlo evidence, the proposed approximations are more efficient than crude Monte Carlo.
Keywords:Extreme value theory  Generalized beta distribution  Lognormal mixture  Probability-weighted moments  Random sum
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号