The estimation of risk at extreme levels of significance (such as 0.1%) can be crucial to capture the losses during market downturns, such as the global financial crisis and the COVID-19 market crash. For many existing models, it is challenging to estimate risk at extreme levels of significance....

We employ a large dataset of physical inventory data on 21 different commodities for the period 1993-2011 to empirically analyze the behaviour of commodity prices and their volatility as predicted by the theory of storage. We examine two main issues. First, we analyze the relationship between...