Vector-Valued Multivariate Conditional Value-at-Risk
arXiv:1708.01324 · doi:10.1016/j.orl.2018.02.006
Abstract
In this study, we propose a new definition of multivariate conditional value-at-risk (MCVaR) as a set of vectors for discrete probability spaces. We explore the properties of the vector-valued MCVaR (VMCVaR) and show the advantages of VMCVaR over the existing definitions given for continuous random variables when adapted to the discrete case.