Average Value at Risk in Fuzzy Risk Analysis

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.

[1]  Stephen M. Roberts Practical Issues in the Use of Probabilistic Risk Assessment , 1999 .

[2]  Guy Kaplanski,et al.  VAR Risk Measures Versus Traditional Risk Measures: An Analysis and Survey , 2001 .

[3]  R. Tyrrell Rockafellar,et al.  Coherent Approaches to Risk in Optimization Under Uncertainty , 2007 .

[4]  Shyi-Ming Chen,et al.  Fuzzy risk analysis based on fuzzy numbers with different shapes and different deviations , 2008, Expert Syst. Appl..

[5]  Philippe Artzner,et al.  Coherent Measures of Risk , 1999 .

[6]  Jinwu Gao,et al.  The Independence of Fuzzy Variables with Applications to Fuzzy Random Optimization , 2007, Int. J. Uncertain. Fuzziness Knowl. Based Syst..

[7]  Phhilippe Jorion Value at Risk: The New Benchmark for Managing Financial Risk , 2000 .

[8]  Jin Peng,et al.  Fuzzy Dominance Based on Credibility Distributions , 2005, FSKD.

[9]  Jin Peng,et al.  Ranking Fuzzy Variables in Terms of Credibility Measure , 2006, FSKD.

[10]  Shouyang Wang,et al.  Progress in Risk Measurement 1 , 2004 .

[11]  Moorad Choudhry,et al.  An Introduction to Value-at-Risk , 1999 .

[12]  Claudio Moraga,et al.  A Fuzzy Risk Model and Its Matrix Algorithm , 2002, Int. J. Uncertain. Fuzziness Knowl. Based Syst..

[13]  Guy Kaplanski,et al.  VaR Risk Measures versus Traditional Risk Measures: an Analysis and Survey , 2002 .

[14]  Olivier Scaillet,et al.  Sensitivity Analysis of Values at Risk , 2000 .

[15]  Michael E. Ginevan A Review of Environmental Stats for S-Plus , 1999 .

[16]  Jun-ya Gotoh,et al.  Newsvendor solutions via conditional value-at-risk minimization , 2007, Eur. J. Oper. Res..

[17]  Xiang Li,et al.  A Sufficient and Necessary Condition for Credibility Measures , 2006, Int. J. Uncertain. Fuzziness Knowl. Based Syst..

[18]  R. Rockafellar,et al.  Optimization of conditional value-at risk , 2000 .

[19]  Baoding Liu,et al.  A survey of credibility theory , 2006, Fuzzy Optim. Decis. Mak..

[20]  D. Duffie,et al.  An Overview of Value at Risk , 1997 .

[21]  Baoding Liu Uncertainty Theory: An Introduction to its Axiomatic Foundations , 2004 .

[22]  Olivier Scaillet,et al.  Sensitivity Analysis of VAR Expected Shortfall for Portfolios Under Netting Agreements , 2003 .

[23]  Jin Peng Measuring Fuzzy Risk by Credibilistic Value at Risk , 2008, 2008 3rd International Conference on Innovative Computing Information and Control.

[24]  Baoding Liu,et al.  Some properties of optimistic and pessimistic values of fuzzy variables , 2004, 2004 IEEE International Conference on Fuzzy Systems (IEEE Cat. No.04CH37542).

[25]  T. Coleman,et al.  Minimizing CVaR and VaR for a portfolio of derivatives , 2006 .

[26]  Olivier Scaillet,et al.  Sensitivity Analysis of VaR Expected Shortfall for Portfolios Under Netting Agreements , 2003 .

[27]  Yian-Kui Liu,et al.  Expected value of fuzzy variable and fuzzy expected value models , 2002, IEEE Trans. Fuzzy Syst..

[28]  Stanislav Uryasev,et al.  Conditional Value-at-Risk for General Loss Distributions , 2002 .

[29]  Shyi-Ming Chen,et al.  Fuzzy risk analysis based on the ranking of generalized trapezoidal fuzzy numbers , 2007, Applied Intelligence.

[30]  Shyi-Ming Chen,et al.  Fuzzy risk analysis based on similarity measures of generalized fuzzy numbers , 2003, IEEE Trans. Fuzzy Syst..

[31]  Lotfi A. Zadeh,et al.  Fuzzy Sets , 1996, Inf. Control..