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Estimating the conditional tail index by integrating a kernel conditional quantile estimator |
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| Authors: | L Gardes A Guillou A Schorgen |
| Institution: | 1. INRIA Rhône-Alpes, projet Mistis, Inovallée, 655 av. de l''Europe, 38334 Montbonnot, Saint-Ismier cedex, France;2. Université de Strasbourg et CNRS, IRMA, UMR 7501, 7 rue René Descartes, 67084 Strasbourg cedex, France |
| Abstract: | This paper deals with the estimation of the tail index of a heavy-tailed distribution in the presence of covariates. A class of estimators is proposed in this context and its asymptotic normality established under mild regularity conditions. These estimators are functions of a kernel conditional quantile estimator depending on some tuning parameters. The finite sample properties of our estimators are illustrated on a small simulation study. |
| Keywords: | Heavy-tailed distribution Covariates Kernel estimator Asymptotic normality |
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