A general stochastic model for bivariate episodes driven by a gamma sequence

Journal of Statistical Distributions and Applications

Charles K. Amponsah¹  Tomasz J. Kozubowski¹  Anna K. Panorska¹ 

[1] Department of Mathematics & Statistics, University of Nevada, Reno, USA;

关键词: BEG model;    Distribution theory;    Heavy tail;    Financial data;    Maximum likelihood estimation;    Power law;    Random summation;    60E05;    62E10;    62E15;    62F10;    62H05;    62H12;    62P05;   

DOI  :  10.1186/s40488-021-00120-5

来源: Springer

【 摘 要 】

We propose a new stochastic model describing the joint distribution of (X,N), where N is a counting variable while X is the sum of N independent gamma random variables. We present the main properties of this general model, which include marginal and conditional distributions, integral transforms, moments and parameter estimation. We also discuss in more detail a special case where N has a heavy tailed discrete Pareto distribution. An example from finance illustrates the modeling potential of this new mixed bivariate distribution.

【 授权许可】

CC BY