RT Report
T1 A dominance approach for comparing the performance of VaR forecasting models
A1 Garcia-Jorcano, Laura
A1 Novales Cinca, Alfonso Santiago
AB We introduce three dominance criteria to compare the performance of alternative VaR forecasting models. The three criteria use the information provided by a battery of VaR validation tests based on the frequency and size of exceedances, offering the possibility of efficiently summarizing a large amount of statistical information. They do not require the use of any loss function defined on the difference between VaR forecasts and observed returns, and two of the criteria are not conditioned on any significance level for the VaR tests. We use them to explore the potential for 1-day ahead VaR forecasting of some recently proposed asymmetric probability distributions for return innovations, as well as to compare the APARCH and FGARCH volatility specifications with more standard alternatives. Using 19 assets of different nature, the three criteria lead to similar conclusions, suggesting that the unbounded Johnson SU, the skewed Student-t and the skewed Generalized-t distributions seem to produce the best VaR forecasts. The added flexibility of a free power parameter in the conditional volatility in the APARCH and FGARCH models leads to a better fit to return data, but it does not improve upon the VaR forecasts provided by GARCH and GJR-GARCH volatilities.
PB Facultad de Ciencias Económicas y Empresariales. Instituto Complutense de Análisis Económico (ICAE)
SN 2341-2356
YR 2019
FD 2019
LK https://hdl.handle.net/20.500.14352/17510
UL https://hdl.handle.net/20.500.14352/17510
LA eng
NO Preprint submitted to Journal of International Financial Markets, Institutions & Money.	May 6, 2019.
DS Docta Complutense
RD 9 abr 2025