In the literature, there is no consensus as to which Value-at-Risk forecasting model is the best for measuring market risk in banks. In the study an analysis of Value-at-Risk forecasting model quality over varying economic stability periods for main indices from stock exchanges was conducted....

This paper revisits the performance of frequently used risk forecasting methods, such as the Value-at-Risk models. The aim is to analyze its performance, and mitigate its pitfalls by incorporating conditional variance estimates, as generated by a GARCH model. Notably, this paper tests several...

The purpose of this paper is to develop a new and simple backtesting procedure that extends the previous work into the multivariate framework. We propose to use the multivariate Portmanteau statistic of Ljung-Box type to jointly test for the absence of autocorrelations and cross-correlations in...

VaR remains important in market risk management as Basel keeps most of the backtesting based on 1% VaR. Comparative backtesting as practiced in the current literature suffers from a major double problem. On the one hand, the score functions, although strictly consistent, may assign very good or...

We study a class of backtests for forecast distributions in which the test statistic is a spectral transformation that weights exceedance events by a function of the modeled probability level. The choice of the kernel function makes explicit the user's priorities for model performance. The class...

The empirical joint distribution of return-pairs on stock indices displays high tail-dependence in the lower tail and low tail-dependence in the upper tail. The presence of tail-dependence is not compatible with the assumption of (conditional) joint normality. The presence of asymmetric-tail...