B1640
Title: Accurate ways to measure risks of extreme events
Authors: Frederico Caeiro - NOVA.ID.FCT - Universidade Nova de Lisboa (Portugal)
Fernanda Otilia Figueiredo - FFCUL, Universidade de Lisboa, CEAUL (Portugal)
Ligia Henriques-Rodrigues - University of Sao Paulo (Brazil)
Ivette Gomes - FCiencias.ID, Universidade de Lisboa and CEAUL (Portugal) [presenting]
Abstract: Among the great variety of alternative methodologies available to deal with the management of risks of extreme events, and for stationary sequences from a model $F(\cdot)$, with a heavy right tail function, i.e. a positive extreme value index (EVI), the value at risk (VaR) and the conditional tail expectation (CTE) will be under discussion. For these Pareto-type models, the classical EVI-estimators are the Hill (H) estimators, and hence the possibility of considering associated H VaR and CTE-estimators. Since H can be replaced by any consistent EVI-estimator, improvements in the performance of the H CTE-estimators, through the use of reliable EVI-estimators based on different generalised means, are now suggested and studied, both asymptotically and for finite samples.
