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The Mekong—applications of value at risk (VaR) and conditional value at risk (CVaR) simulation to the benefits, costs and consequences of water resources development in a large river basin

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  • Webby, R.B.
  • Adamson, P.T.
  • Boland, J.
  • Howlett, P.G.
  • Metcalfe, A.V.
  • Piantadosi, J.

Abstract

Conditional value at risk (CVaR) was developed as a coherent measure of expected loss given that actual loss exceeds some value at risk (VaR) threshold. To date the concept has been primarily used to support quantitative risk assessment for investment decisions and portfolio management, using stochastic financial models to minimise the risk of unacceptable monetary loss. Intriguingly, the models and concepts are potentially adaptable to water resources planning and operational problems. This paper explores the application of CVaR within the context of identifying the risk of macro-economic damage to the fishery resources of Tonle Sap given reduced volumes of flow on the mainstream Mekong during the flood season. Emphasis is placed on simulating the linkages between the seasonally available flows in the Mekong mainstream, Tonle Sap water levels, annual fish catch and its economic value.

Suggested Citation

  • Webby, R.B. & Adamson, P.T. & Boland, J. & Howlett, P.G. & Metcalfe, A.V. & Piantadosi, J., 2007. "The Mekong—applications of value at risk (VaR) and conditional value at risk (CVaR) simulation to the benefits, costs and consequences of water resources development in a large river basin," Ecological Modelling, Elsevier, vol. 201(1), pages 89-96.
    • Handle: RePEc:eee:ecomod:v:201:y:2007:i:1:p:89-96
    DOI: 10.1016/j.ecolmodel.2006.07.033
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    References listed on IDEAS

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    1. Philippe Artzner & Freddy Delbaen & Jean‐Marc Eber & David Heath, 1999. "Coherent Measures of Risk," Mathematical Finance, Wiley Blackwell, vol. 9(3), pages 203-228, July.
    2. Rockafellar, R. Tyrrell & Uryasev, Stanislav, 2002. "Conditional value-at-risk for general loss distributions," Journal of Banking & Finance, Elsevier, vol. 26(7), pages 1443-1471, July.
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    Cited by:

    1. Jaume Belles‐Sampera & Montserrat Guillén & Miguel Santolino, 2014. "Beyond Value‐at‐Risk: GlueVaR Distortion Risk Measures," Risk Analysis, John Wiley & Sons, vol. 34(1), pages 121-134, January.
    2. L. Shao & X. Qin & Y. Xu, 2011. "A Conditional Value-at-Risk Based Inexact Water Allocation Model," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 25(9), pages 2125-2145, July.
    3. Nafiseh Bahrami & Mohammad Reza Nikoo & Ghazi Al-Rawas & Khalifa Al-Jabri & Amir H. Gandomi, 2023. "Optimal Treated Wastewater Allocation Among Stakeholders Based on an Agent-based Approach," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 37(1), pages 135-156, January.
    4. Jaume Belles-Sampera & Montserrat Guillén & Miguel Santolino, 2013. "“Beyond Value-at-Risk: GlueVaR Distortion Risk Measures”," IREA Working Papers 201302, University of Barcelona, Research Institute of Applied Economics, revised Feb 2013.
    5. Chunhua Tang & Huiyuan Zhang & Jiamuyan Xie, 2022. "Optimal Contract Design in Contract Farming under Asymmetric Effort Information," Sustainability, MDPI, vol. 14(22), pages 1-17, November.
    6. Reus, Lorenzo & Pagnoncelli, Bernardo & Armstrong, Margaret, 2019. "Better management of production incidents in mining using multistage stochastic optimization," Resources Policy, Elsevier, vol. 63(C), pages 1-1.

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