Typically, point forecasting methods are compared and assessed by means of an error
measure or scoring function, with the absolute error and the squared error being key …

In this article we present a theoretical review of the existing literature on Value at Risk (VaR)
specifically focussing on the development of new approaches for its estimation. We effect a …

In econometric applications, often several hypothesis tests are carried out at once. The
problem then becomes how to decide which hypotheses to reject, accounting for the …

Given the growing need for managing financial risk, risk prediction plays an increasing role
in banking and finance. In this study we compare the out-of-sample performance of existing …

In this paper, we compare the performance of a daily ARCH type model (which uses daily
returns) with the performance of a model based on the daily realized volatility (which uses …

This paper evaluates the model risk of models used for forecasting systemic and market risk.
Model risk, which is the potential for different models to provide inconsistent outcomes, is …

This paper considers the properties of risk measures, primarily value-at-risk (VaR), from both
internal and external (regulatory) points of view. It is argued that since market data is …

Knowledge of the statistical distribution of the prices of emission allowances, and their
forecastability, are crucial in constructing, among other things, purchasing and risk …

The interest in forecasting the Value at Risk (VaR) has been growing over the last two
decades, due to the practical relevance of this risk measure for financial and insurance …

This paper offers a new approach to estimating time-varying covariance matrices in the
framework of the diagonal-vech version of the multivariate GARCH (1, 1) model. Our method …