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A0236
Title: Exponential tilts for heteroscedastic extremes with an application to cryptocurrency markets Authors:  Miguel de Carvalho - School of Mathematics, The University of Edinburgh (United Kingdom) [presenting]
Raphael Huser - King Abdullah University of Science and Technology (Saudi Arabia)
Rodrigo Rubio - Pontificia Universidad Catolica de Chile (Chile)
Abstract: A density ratio model is proposed for modeling extreme values of non-identically distributed observations. The proposed model can be regarded as a proportional tails model for multisample settings. A semiparametric specification is devised so to link all elements in a family of scedasis densities through a tilt from a baseline scedasis. Inference is conducted by empirical likelihood inference methods. An application is given to model the dynamics of the frequency of extreme losses of some leading cryptocurrencies.