出版社：Fundação Getulio Vargas, Escola de Pós-Graduação em Economia
摘要：This paper is concerned with evaluating value at risk estimates. It is well
known that using only binary variables to do this sacrifices too much
information. However, most of the specification tests (also called backtests)
avaliable in the literature, such as Christoffersen (1998) and Engle and
Maganelli (2004) are based on such variables. In this paper we propose a new
backtest that does not realy solely on binary variable. It is show that the new
backtest provides a sufficiant condition to assess the performance of a quantile
model whereas the existing ones do not. The proposed methodology allows us to
identify periods of an increased risk exposure based on a quantile regression
model (Koenker & Xiao, 2002). Our theorical findings are corroborated
through a monte Carlo simulation and an empirical exercise with daily S&P500
time series.
