This paper presents a new tool for validating Value-at-Risk (VaR) models. This tool, called the Risk Map, jointly accounts for the number and the magnitude of the VaR exceptions and graphically summarizes all information about the performance of a risk model. It relies on the concept of VaR...

This paper proposes a new duration-based backtesting procedure for VaR forecasts. The GMM test framework proposed by Bontemps (2006) to test for the distributional assumption (i.e. the geometric distribution) is applied to the case of the VaR forecasts validity. Using simple J-statistic based on...