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Asymptotic Bounds for the Distribution of the Sum of Dependent Random Variables
- 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.
- Subjects :
- Statistics and Probability
General Mathematics
Structure (category theory)
Value (computer science)
91E30
01 natural sciences
value at risk
Combinatorics
010104 statistics & probability
0502 economics and business
60E05
Limit (mathematics)
0101 mathematics
Mathematics
Discrete mathematics
050208 finance
05 social sciences
Expected shortfall
Distribution (mathematics)
Dependence bound
complete mixability
modeling uncertainty
60E15
Marginal distribution
Statistics, Probability and Uncertainty
Random variable
Value at risk
Subjects
Details
- ISSN :
- 14756072 and 00219002
- Volume :
- 51
- Database :
- OpenAIRE
- Journal :
- Journal of Applied Probability
- Accession number :
- edsair.doi.dedup.....31c7ce065b8abac7613e3a56020fb0e9