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Risk metrics of loss function for uncertain system

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Abstract

Real-life decisions are usually made in the state of uncertainty or risk. In this article we present two types of risk metrics of loss function for uncertain system. Firstly, the concept of value at risk (VaR) of loss function is introduced based on uncertainty theory and its fundamental properties are examined. Then the tail value at risk (TVaR) concept of loss function is evolved and some fundamental properties of the proposed TVaR are investigated. Both the VaR and TVaR are harmonious risk metrics. The suggested VaR or TVaR methodology can be widely used as tools of risk analysis in uncertain environments.

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References

  • Acerbi C., Tasche D. (2002) On the coherence of expected shortfall. Journal of Banking and Finance 26: 1487–1503

    Article  Google Scholar 

  • Bedford T., Cooke R.M. (2001) Probabilistic risk analysis: Foundations and methods. Cambridge University Press, Cambridge, MA

    Book  MATH  Google Scholar 

  • Choudhry M. (2006) An introduction to value-at-risk (4th ed.). Wiley, London

    Google Scholar 

  • Desmedt S., Jean-Francois W. (2008) On the subaddivity of tail value at risk: An investigation with copulas. Variance 2(2): 231–252

    Google Scholar 

  • Jorion P. (2001) Value at risk: The new benchmark for managing financial risk (2nd ed.). McGraw- Hill, New York

    Google Scholar 

  • Kolmogorov A. N. (1933) Grundbegriffe der Wahrscheinlichkeitsrechnung. Springer, Berlin

    Google Scholar 

  • Liu B. (2007) Uncertainty theory (2nd ed.). Springer, Berlin

    MATH  Google Scholar 

  • Liu B. (2009) Some research problems in uncertainty theory. Journal of Uncertain Systems 3(1): 3–10

    Google Scholar 

  • Liu B. (2010a) Uncertain risk analysis and uncertain reliability analysis. Journal of Uncertain Systems 4(3): 163–170

    Google Scholar 

  • Liu B. (2010b) Uncertainty theory: A branch of mathematics for modeling human uncertainty. Springer, Berlin

    Google Scholar 

  • Liu B. (2012) Why is there a need for uncertainty theory?. Journal of Uncertain Systems 6(1): 3–10

    Google Scholar 

  • Morgan J. P. (1996) Risk metrics TM—technical document (4th ed.). Morgan Guaranty Trust Companies, New York

    Google Scholar 

  • Rockafeller R. T., Uryasev S. (2001) Conditional value-at-risk for general loss distributions. Journal of Banking and Finance 26(7): 1443–1471

    Article  Google Scholar 

  • Rosenberg J. V., Til S. (2006) A general approach to integrated risk management with skewed, fat-tailed risks. Journal of Financial Economics 79: 569–614

    Article  Google Scholar 

  • Yamai Y., Yoshiba T. (2005) Value-at-risk versus expected shortfall: A practical perspective. Journal of Banking and Finance 29(4): 997–1015

    Article  Google Scholar 

  • Zadeh L. A. (1965) Fuzzy sets. Information and Control 8: 338–353

    Article  MathSciNet  MATH  Google Scholar 

Download references

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Correspondence to Jin Peng.

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Peng, J. Risk metrics of loss function for uncertain system. Fuzzy Optim Decis Making 12, 53–64 (2013). https://doi.org/10.1007/s10700-012-9146-5

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