This paper proposes improvements to advanced measurement approach (AMA) to estimating operational risks, and applies the improved methods to US business losses categorised into five business lines and three event types operational losses. The AMA involves, among others, modelling a loss severity...

This paper proposes some improvements to advanced measurement approach (AMA) to modelling operational losses and applies this approach to US business losses. The AMA involves, among others, modelling a loss severity distribution and estimating its Expected Loss and the 99.9% operational...

This paper employs methodologies that were developed for heavy right-tailed distributions to construct the point and interval estimates of the expected operational losses in the US. These are consistent and unbiased estimates of the mean of the heavy right-tailed loss distribution, whereas those...

This paper presents a new method for synthesizing instrumental variables using only the dependent and endogenous explanatory variables of the regression model. We show that a valid instruments can be spanned using the dependent and endogenous variables. Then based on this rationale, we construct...

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...