| Institution: | 1.Department of Statistical Sciences,University of Padua,Padua,Italy;2.Dipartimento di Scienze dell’Economia,Università del Salento,Lecce,Italy;3.Institute of Mathematics,University of Warsaw,Warsaw,Poland;4.Department MEMOTEF,Sapienza University of Rome,Rome,Italy;5.Dipartimento di Matematica e Fisica,Università del Salento,Lecce,Italy |
| Abstract: | We present a novel methodology to compute conditional risk measures when the conditioning event depends on a number of random variables. Specifically, given a random vector \((\mathbf {X},Y)\), we consider risk measures that express the risk of Y given that \(\mathbf {X}\) assumes values in an extreme multidimensional region. In particular, the considered risky regions are related to the AND, OR, Kendall and Survival Kendall hazard scenarios that are commonly used in environmental literature. Several closed formulas are considered (especially in the AND and OR scenarios). An application to spatial risk analysis involving real data is discussed. |
