Tag Archives: kernel

Estimation de quantile par noyau beta

Le papier sur l’estimation de quantile par noyau beta, coécrit avec Abder Oulidi, est accepté pour publication dans Statistics and Computing, http://link.springer.com/…

In this paper we propose several nonparametric estimators of quantiles based on Beta kernel and applied to transformed data by the generalized Champernowne distribution initially fitted to the data. A Monte-Carlo based study will show that those estimators improve the efficiency of a traditional ones, not only for light tailed distributions, but also heavy tails, when the probability level is close to 1. We also compare these estimators with the Extreme Value Theory Quantile applying to Danish data on large fire insurance losses.

Talk on Value-at-Risk estimation

Exposé au séminaire d’Actuariat, à la faculté de Sciences Economiques à Amsterdam (UvA). L’exposé portera sur l’estimation de quantiles (et de Value-at-Risk) sur des données de pertes, avec une application de gestion de portefeuille moyenne-VaR.

In this talk we propose several nonparametric estimators of quantiles based on Beta kernel and applied to transformed data by the generalized Champernowne distribution initially fitted to the data. A Monte-Carlo based study will show that those estimators improve the efficiency, not only for light tailed distributions, but mainly for heavy tailed, when the probability level is close to 1.Another application will be seen, on portfolio optimization in the mean-VaR context.