In risk management areas such as reinsurance, the need often arises to construct a confidence interval for a quantile in the tail of the distribution; for example, there is high probability that the sample maximum lies near or below the quantile. While different methods, including subsample...

We develop a method for constructing prediction intervals for a nonstationary variable, such as GDP. The method uses a factor augmented regression [FAR] model. The predictors in the model includes a small number of factors generated to extract most of the information in a set of panel data on a...

We develop a method for constructing prediction intervals for a nonstationary variable, such as GDP. The method uses a factor augmented regression [FAR] model. The predictors in the model includes a small number of factors generated to extract most of the information in a set of panel data on a...

This paper investigates stock-bond portfolios’ tail risks such as value-at-risk (VaR) and expected shortfall (ES), and the way in which these measures have been affected by the global financial crisis. The semiparametric t-copula is found to be adequate for modelling stock-bond joint...

This paper investigates stock–bond portfolios' tail risks such as value-at-risk (VaR) and expected shortfall (ES), and the way in which these measures have been affected by the global financial crisis. The semiparametric t-copulas adequately model stock–bond returns joint distributions of G7...