DPOT methodology - an application to Value-at-Risk

Threshold methods, based on fitting a stochastic model to the excesses over a threshold, were developed under the acronym POT (peaks over threshold). In order to eliminate the tendency to clustering of violations, a model based approach within the POT framework, that uses the durations between excesses as covariates, is presented. Based on this approach, models for forecasting one-day-ahead Valueat-Risk were applied to Standard & Poor’s 500 Index. Comparative studies provide evidence that they can perform better than state-of-the art risk models.