Bayesian inference for extreme quantiles of heavy tailed distributions

We propose a new method for estimating extremes quantiles of a wide class of heavy-tailed distributions. Our proposal makes Bayesian inference on extreme quantiles through High Posterior Density intervals. We evaluate the performance of the proposal by numerical results.