| Titre : | Evaluating value-at-risk models with desk-level data (2012) |
| Auteurs : | Jeremy Berkowitz, Auteur ; Peter Christoffersen ; Denis Pelletier, Auteur |
| Type de document : | Article : texte imprimé |
| Dans : | Management science (Vol. 57 N° 12, Décembre 2011) |
| Article en page(s) : | pp. 2213-2227 |
| Note générale : | Management |
| Langues : | Anglais |
| Tags : | Risk management Backtesting Volatility Disclosure |
| Résumé : | We present new evidence on disaggregated profit and loss (P/L) and value-at-risk (VaR) forecasts obtained from a large international commercial bank. Our data set includes the actual daily P/L generated by four separate business lines within the bank. All four business lines are involved in securities trading and each is observed daily for a period of at least two years. Given this unique data set, we provide an integrated, unifying framework for assessing the accuracy of VaR forecasts. We use a comprehensive Monte Carlo study to assess which of these many tests have the best finite-sample size and power properties. Our desk-level data set provides importance guidance for choosing realistic P/L-generating processes in the Monte Carlo comparison of the various tests. The conditional autoregressive value-at-risk test of Engle and Manganelli (2004) performs best overall, but duration-based tests also perform well in many cases. |
| DEWEY : | 658 |
| ISSN : | 0025-1909 |
| En ligne : | http://mansci.journal.informs.org/content/57/12/2213.abstract |
