Por Gilles Stupfler (University of Angers, France).
Expectiles were originally introduced by Newey and Powell (Econometrica 1987) in order to test for symmetry in heteroskedastic regression models. They have recently seen a regain of interest due to the nice properties they have in the context of risk assessment in insurance and finance. I will discuss the definition of expectiles, some of their most important properties, and recent work around their estimation and inference at extreme levels. I will illustrate the results on actuarial and financial data.
Short bio: Gilles Stupfler is a Professor of Statistics in the Laboratoire Angevin de REcherche en MAthématiques (LAREMA, University of Angers, France.
He is the creator and current editor of the Extreme Value Analysis newsletter, written for the worldwide academic extreme value community, with regular information about conferences, workshops, and events as well as offers for Ph.D. and post-doctoral fellowships in the area of probabilistic and statistical extreme value analysis.
Gilles Stupfler’s area of research is extreme value analysis. Much of his recent work in this direction has focused on how to measure and estimate extreme risk, particularly in actuarial and financial contexts. His work generally sits at the interface of extreme value theory and various subfields of statistics, such as semi- and non-parametric regression, M-estimation, missing data frameworks, and Estimation with stationary but dependent data.
Transmissão via Zoom.
