Value-at-Risk vs. Conditional Value-at-Risk in Risk Management and Optimization

By Sergey Sarykalin. 2008

421 citations recorded by the source corpus.

From the mathematical perspective considered in this tutorial, risk management is a procedure for shaping a risk distribution. Popular functions managing risk are valueat-risk (VaR) and conditional value-at-risk (CVaR). The problem of choice between VaR and CVaR, especially in financial risk management, has been quite popular in academic literature. Reasons affecting the choice between VaR and CVaR are based on the differences in mathematical properties, stability of statistical estimation, simplicity of optimization procedures, acceptance by regulators, etc. This tutorial presents our personal experience working with these key percentile risk measures. We try to explain strong and weak features of these risk measures and illustrate them with several examples. We demonstrate risk management/optimization case studies conducted with the Portfolio Safeguard package.

Subfields: Demography, Finance, Management Science and Operations Research

View Paper: https://www.semanticscholar.org/paper/a5df128eed59668b525a743a4e7f3f0efe12f930

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Citations in the corpus

Supply chain resilience for single and multiple sourcing in the presence of disruption risks (2018, background): “C-VaR and VaR connect the extent of loss to the probability of its causes (Rockafellar and Uryasev 2000; Rockafellar and Uryasev 2002; Sarykalin, Serraino, and Uryasev 2008).”
Chance-Constrained Two-Stage Unit Commitment Under Uncertain Load and Wind Power Output Using Bilinear Benders Decomposition (2016, background): “Indeed, chance constraint usually introduces non-convexity into the original model while CVaR preserves convexity [33].”
Incorporating risk measures in closed-loop supply chain network design (2014, methodology): “In addition, in our mathematical approach, risk management is a procedure to shape risk distribution (Sarykalin, Serraino, and Uryasev 2008).”
A critical review on supply chain risk – Definition, measure and modeling ☆ (2015, background): “Developed by Rockafellar and Uryasev CVaR attracts much attention due to its mathematical properties that are especially suitable for optimization problems [118,121].”