3 accepted papers
In this paper, we develop a new method for estimating the tail-index found in extreme value statistics. Using a fixed quantile, model-selection approach, we derive the posterior distribution of the tail-index marginalizing out the unknown threshold and nuisance parameters. Our marginalized threshold…
In this paper, we propose a new approach for analyzing extreme values that are witnessed in financial markets. Our goal is to compute the predictive distribution of extreme events that are clustered in time and, as opposed to modeling just the maximum of a block of observations, we model the conditi…
In this paper, we propose a new approach for analyzing extreme values such as large losses in financial markets. Our goal is to compute the predictive distribution of extreme events that are clustered in time. We apply a stochastic parametrization of the generalized extreme value distribution to mod…