On distributional robust probability functions and their computations

Man Hong Wong; Shuzhong Zhang

doi:10.1016/j.ejor.2013.08.044

On distributional robust probability functions and their computations

Man Hong Wong, Shuzhong Zhang

Industrial and Systems Engineering

Research output: Contribution to journal › Article › peer-review

Abstract

Consider a random vector, and assume that a set of its moments information is known. Among all possible distributions obeying the given moments constraints, the envelope of the probability distribution functions is introduced in this paper as distributional robust probability function. We show that such a function is computable in the bi-variate case under some conditions. Connections to the existing results in the literature and its applications in risk management are discussed as well.

Original language	English (US)
Pages (from-to)	23-33
Number of pages	11
Journal	European Journal of Operational Research
Volume	233
Issue number	1
DOIs	https://doi.org/10.1016/j.ejor.2013.08.044
State	Published - Feb 16 2014

Bibliographical note

Funding Information:
Research of the second author was supported in part by the US National Science Foundation under Grant No. CMMI-1161242 .

Keywords

Conic programming
Distributional robust
Moment bounds
Risk management
Semidefinite programming (SDP)

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10.1016/j.ejor.2013.08.044

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abstract = "Consider a random vector, and assume that a set of its moments information is known. Among all possible distributions obeying the given moments constraints, the envelope of the probability distribution functions is introduced in this paper as distributional robust probability function. We show that such a function is computable in the bi-variate case under some conditions. Connections to the existing results in the literature and its applications in risk management are discussed as well.",

keywords = "Conic programming, Distributional robust, Moment bounds, Risk management, Semidefinite programming (SDP)",

author = "Wong, {Man Hong} and Shuzhong Zhang",

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N2 - Consider a random vector, and assume that a set of its moments information is known. Among all possible distributions obeying the given moments constraints, the envelope of the probability distribution functions is introduced in this paper as distributional robust probability function. We show that such a function is computable in the bi-variate case under some conditions. Connections to the existing results in the literature and its applications in risk management are discussed as well.

AB - Consider a random vector, and assume that a set of its moments information is known. Among all possible distributions obeying the given moments constraints, the envelope of the probability distribution functions is introduced in this paper as distributional robust probability function. We show that such a function is computable in the bi-variate case under some conditions. Connections to the existing results in the literature and its applications in risk management are discussed as well.

KW - Conic programming

KW - Distributional robust

KW - Moment bounds

KW - Risk management

KW - Semidefinite programming (SDP)

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ER -

On distributional robust probability functions and their computations

Abstract

Bibliographical note

Keywords

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