We propose independence and conditional coverage tests aimed at evaluating the accuracy of Value-at-Risk (VaR) forecasts from the same model at different confidence levels. The proposed procedures are multilevel tests, i.e. joint tests of several quantiles corresponding to different confidence levels. In a comprehensive Monte Carlo exercise, we document the superiority of the proposed tests with respect to existing multilevel tests. In an empirical application, we illustrate the implementation of the tests using several VaR models and daily data for 15 MSCI world indices.
Scheda prodotto non validato
Attenzione! I dati visualizzati non sono stati sottoposti a validazione da parte dell'ateneo
Titolo: | Evaluating the Accuracy of Value-at-Risk Forecasts: New Multilevel Tests |
Autori: | |
Data di pubblicazione: | 2014 |
Rivista: | |
Handle: | http://hdl.handle.net/20.500.11770/134611 |
Appare nelle tipologie: | 1.1 Articolo in rivista |