Forecasting one-day-ahead Value-at-Risk with a Duration based POT method

Threshold methods, based on fltting 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 proposed. Based on this approach, two models for forecasting one-day-ahead Value-at-Risk were suggested and applied to real data. Comparative studies provides evidence that they can perform better than state-of-the art risk models, both in terms of out-of-sample accuracy and minimization of capital requirements under the Basel II Accord.

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