RT Monograph
SR 00
A1 Bontemps, Christian
T1 Simple moment-based tests for value-at-risk models and discrete distribution
YR 2014
FD 2014-10-15
VO 14-535
SP 76
K1 moment-based tests
K1 parameter uncertainty
K1 discrete distributions
K1 value-at-risk
K1 backtesting
AB In this paper, we develop moment-based tests for parametric discrete distributions. Momentbased test techniques are attractive as they provide easy-to-implement test statistics. We propose a general transformation that makes the moments of interest insensitive to the parameter estimation uncertainty. This transformation is valid for some extended families of non-differentiable moments that are of great interest in the case of discrete distributions. Considering the power function under local alternatives, we compare this strategy with the one in which parameter uncertainty is corrected. The special example of backtesting of valueat- risk (VaR) forecasts is treated in detail, and we provide simple moments that have good size and power properties in Monte Carlo experiments. Additional examples considered are discrete counting processes and the geometric distribution. We finally apply our method to backtesting of VaR forecasts derived from a T-GARCH(1,1) model estimated using foreign exchange-rate data.
T2 TSE Working Paper
PB TSE Working Paper
PP Toulouse
AV Published
LK https://publications.ut-capitole.fr/id/eprint/16617/
UL http://tse-fr.eu/pub/28749