Heavy Tailed Estimation in Stochastic Differential Equations With An Application

Document Type : Primary Research paper


Department of Statistics, College of Administration and Economics, University of Al-Qadisiyah, Diwaniyah, Iraq.


Heavy-tailed distributions are very important branch in statistical analysis. In this paper, we will estimate the tail parameter (a) using three (the Direct, Bootstrap and Double Bootstrap) methods in two examples of Stochastic Differential Equations driven by (Brownian Motion and Levy Process). Our aim is to illustrate the best way to estimate the
a-stable with (0<a<2) using simulation and real data for the daily Iraqi financial market dataset.