Conditional Value-at-Risk for General Loss Distributions

@article{Rockafellar2001ConditionalVF,
  title={Conditional Value-at-Risk for General Loss Distributions},
  author={R. T. Rockafellar and S. Uryasev},
  journal={Social Science Research Network},
  year={2001}
}
Fundamental properties of conditional value-at-risk (CVaR), as a measure of risk with significant advantages over value-at-risk (VaR), are derived for loss distributions in finance that can involve discreetness. Such distributions are of particular importance in applications because of the prevalence of models based on scenarios and finite sampling. CVaR is able to quantify dangers beyond VaR and moreover it is coherent. It provides optimization short-cuts which, through linear programming… Expand
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