On Sums of Conditionally Independent Subexponential Random Variables

Authors:
Serguei Foss;Andrew Richards
Affiliations:
School of Mathematics and Computer Sciences and the Maxwell Institute for Mathematical Sciences, Heriot-Watt University, Edinburgh EH14 4AS, UK;School of Mathematics and Computer Sciences and the Maxwell Institute for Mathematical Sciences, Heriot-Watt University, Edinburgh EH14 4AS, UK
Venue:
Mathematics of Operations Research
Year:
2010

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Abstract

The asymptotic tail behaviour of sums of independent subexponential random variables is well understood, one of the main characteristics being the principle of the single big jump. We study the case of dependent subexponential random variables, for both deterministic and random sums, using a fresh approach, by considering conditional independence structures on the random variables. We seek sufficient conditions for the results of the theory with independent random variables to still hold. For a subexponential distribution, we introduce the concept of a boundary class of functions, which we hope will be a useful tool in studying many aspects of subexponential random variables. The examples we give demonstrate a variety of effects owing to the dependence, and are also interesting in their own right.