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Average Value at Risk in Fuzzy Risk Analysis

  • Conference paper
Fuzzy Information and Engineering Volume 2

Part of the book series: Advances in Intelligent and Soft Computing ((AINSC,volume 62))

Abstract

The average value at risk (AVaR) is a risk measure which is a superior alternative to value at risk (VaR). In this paper, we present the average value at risk method for fuzzy risk analysis. Firstly, we put forward the new concept of the average value at risk based on credibility theory. Next, we examine some properties of the proposed average value at risk. Then, a kind of fuzzy simulation algorithm is given to calculate the average value at risk. Finally, numerical example is provided. The proposed average value at risk can be applied in many real problems of fuzzy risk analysis.

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Author information

Authors and Affiliations

  1. Institute of Uncertain Systems, College of Mathematics and Information Sciences, Huanggang Normal University, Hubei, 438000, China

    Jin Peng

Authors
  1. Jin Peng
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Editor information

Editors and Affiliations

  1. Guangzhou University, China

    Bingyuan Cao

  2. Chongqing University of Science and Technology, Chongqing, PR China

    Tai-Fu Li

  3. Hainan Normal University, Hainan, PR China

    Cheng-Yi Zhang

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© 2009 Springer-Verlag Berlin Heidelberg

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Peng, J. (2009). Average Value at Risk in Fuzzy Risk Analysis. In: Cao, B., Li, TF., Zhang, CY. (eds) Fuzzy Information and Engineering Volume 2. Advances in Intelligent and Soft Computing, vol 62. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-03664-4_139

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  • DOI: https://doi.org/10.1007/978-3-642-03664-4_139

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-03663-7

  • Online ISBN: 978-3-642-03664-4

  • eBook Packages: EngineeringEngineering (R0)

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