Asymptotic Tail Probabilities of Sums of Dependent Subexponential Random Variables

Jaap Geluk () and Qihe Tang ()
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Jaap Geluk: The Petroleum Institute
Qihe Tang: The University of Iowa

Journal of Theoretical Probability, 2009, vol. 22, issue 4, 871-882

Abstract: Abstract In this paper we study the asymptotic behavior of the tail probabilities of sums of dependent and real-valued random variables whose distributions are assumed to be subexponential and not necessarily of dominated variation. We propose two general dependence assumptions under which the asymptotic behavior of the tail probabilities of the sums is the same as that in the independent case. In particular, the two dependence assumptions are satisfied by multivariate Farlie-Gumbel-Morgenstern distributions.

Keywords: Asymptotic tail probability; Convolution; Dominated variation; Farlie-Gumbel-Morgenstern family; Subexponentiality; 62E20; 60G70; 62H20 (search for similar items in EconPapers)
Date: 2009
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Citations: View citations in EconPapers (6)

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DOI: 10.1007/s10959-008-0159-5

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