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Asymptotic Bounds for the Distribution of the Sum of Dependent Random Variables

Authors :
Ruodu Wang
Source :
J. Appl. Probab. 51, no. 3 (2014), 780-798
Publication Year :
2014
Publisher :
Cambridge University Press (CUP), 2014.

Abstract

Suppose that X 1, …, X n are random variables with the same known marginal distribution F but unknown dependence structure. In this paper we study the smallest possible value of P(X 1 + · · · + X n < s) over all possible dependence structures, denoted by m n,F (s). We show that m n,F (ns) → 0 for s no more than the mean of F under weak assumptions. We also derive a limit of m n,F (ns) for any s ∈ R with an error of at most n -1/6 for general continuous distributions. An application of our result to risk management confirms that the worst-case value at risk is asymptotically equivalent to the worst-case expected shortfall for risk aggregation with dependence uncertainty. In the last part of this paper we present a dual presentation of the theory of complete mixability and give dual proofs of theorems in the literature on this concept.

Details

ISSN :
14756072 and 00219002
Volume :
51
Database :
OpenAIRE
Journal :
Journal of Applied Probability
Accession number :
edsair.doi.dedup.....31c7ce065b8abac7613e3a56020fb0e9