Weak Limit of the Geometric Sum of Independent But Not Identically Distributed Random Variables

Abstract

We show that when $\set{X_j}$ is a sequence of independent (but not necessarily identically distributed) random variables which satisfies a condition similar to the Lindeberg condition, the properly normalized geometric sum $\sum_{j=1}^{\nu_p}X_j$ (where $\nu_p$ is a geometric random variable with mean $1/p$) converges in distribution to a Laplace distribution as $p\to 0$. The same conclusion holds for the multivariate case. This theorem provides a reason for the ubiquity of the double power law in economic and financial data.