On distributional robust probability functions and their computations

Man Hong Wong, Shuzhong Zhang

Research output: Contribution to journalArticlepeer-review


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 languageEnglish (US)
Pages (from-to)23-33
Number of pages11
JournalEuropean Journal of Operational Research
Issue number1
StatePublished - 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 .


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


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