Credibilistic value and average value at risk in fuzzy risk analysis

Decision making in real world is usually made in fuzzy environment and subject to fuzzy risks. The value at risk (VaR) is a widely used tool in risk management and the average value at risk (AVaR) is a risk measure which is a superior alternative to VaR. In this paper, we present a methodology for fuzzy risk analysis based on credibility theory. First, we present the new concepts of the credibilistic VaR and credibilistic AVaR. Next, we examine some properties of the proposed credibilistic VaR and credibilistic AVaR. After that, a kind of fuzzy simulation algorithms are given to show how to calculate them. Finally, a numerical example is illustrated. The proposed credibilistic VaR and credibilistic AVaR are suitable for use in many real problems of fuzzy risk analysis.