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00925njm 22002777a 4500 dc Belles Sampera, Jaume author Merigó Lindahl, José M. author Guillén, Montserrat author Santolino, Miguel author 2019-01-15T11:39:17Z 2019-01-15T11:39:17Z 2013-03 2019-01-15T11:39:17Z Distortion risk measures summarize the risk of a loss distribution by means of a single value. In fuzzy systems, the Ordered Weighted Averaging (OWA) and Weighted Ordered Weighted Averaging (WOWA) operators are used to aggregate a large number of fuzzy rules into a single value. We show that these concepts can be derived from the Choquet integral, and then the mathematical relationship between distortion risk measures and the OWA and WOWA operators for discrete and finite random variables is presented. This connection offers a new interpretation of distortion risk measures and, in particular, Value-at-Risk and Tail Value-at-Risk can be understood from an aggregation operator perspective. The theoretical results are illustrated in an example and the degree of orness concept is discussed. Presa de decisions (Estadística) Teoria d'operadors Direcció d'empreses Lògica matemàtica Statistical decision Operator theory Industrial management Mathematical logic The connection between distortion risk measures and ordered weighted averaging operators