Gatarek, Lukasz T.
[Verfasser:in]
;
Hoogerheide, Lennart F.
[Sonstige Person, Familie und Körperschaft];
Hooning, Koen
[Sonstige Person, Familie und Körperschaft];
van Dijk, H. K.
[Sonstige Person, Familie und Körperschaft]
Censored Posterior and Predictive Likelihood in Bayesian Left-Tail Prediction for Accurate Value at Risk Estimation
Erschienen in:Tinbergen Institute Discussion Paper 13-060/III
Umfang:
1 Online-Ressource (37 p)
Sprache:
Englisch
DOI:
10.2139/ssrn.2251206
Identifikator:
Entstehung:
Anmerkungen:
Nach Informationen von SSRN wurde die ursprüngliche Fassung des Dokuments March 6, 2013 erstellt
Beschreibung:
Accurate prediction of risk measures such as Value at Risk (VaR) and Expected Shortfall (ES) requires precise estimation of the tail of the predictive distribution. Two novel concepts are introduced that offer a specific focus on this part of the predictive density: the censored posterior, a density for the model parameters that results if we replace the likelihood by a so-called censored likelihood in the posterior; and the censored predictive likelihood, which is used for Model Averaging for forecast combination. We perform extensive experiments involving simulated and empirical data. Our results show the ability of these new approaches to outperform the standard posterior and traditional Bayesian Model Averaging techniques in applications of Value-at-Risk prediction in GARCH models