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Decision tree analysis for a risk averse decision maker: CVaR Criterion

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  • Eskandarzadeh, Saman
  • Eshghi, Kourosh

Abstract

Risk aversion is a prevalent phenomenon when sufficiently large amounts are at risk. In this paper, we introduce a new prescriptive approach for coping with risk in sequential decision problems with discrete scenario space. We use Conditional Value-at-Risk (CVaR) risk measure as optimization criterion and prove that there is an explicit linear representation of the proposed model for the problem.

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  • Eskandarzadeh, Saman & Eshghi, Kourosh, 2013. "Decision tree analysis for a risk averse decision maker: CVaR Criterion," European Journal of Operational Research, Elsevier, vol. 231(1), pages 131-140.
    • Handle: RePEc:eee:ejores:v:231:y:2013:i:1:p:131-140
    DOI: 10.1016/j.ejor.2013.04.033
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    References listed on IDEAS

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    3. Han He & Sicheng Li & Lin Hu & Nelson Duarte & Otilia Manta & Xiao-Guang Yue, 2019. "Risk Factor Identification of Sustainable Guarantee Network Based on Logistic Regression Algorithm," Sustainability, MDPI, vol. 11(13), pages 1-19, June.
    4. Xinsheng Xu & Zhiqing Meng & Ping Ji & Chuangyin Dang & Hongwei Wang, 2016. "On the newsvendor model with conditional Value-at-Risk of opportunity loss," International Journal of Production Research, Taylor & Francis Journals, vol. 54(8), pages 2449-2458, April.

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