Econometric Analysis of Energy and Emissions Markets: Multiple Hypothesis Testing Techniques

Multiple hypothesis testing (MHT) procedures can broadly be categorized as p-value-based approaches that assume the existence of and work on a set of available p-values and resampling-based approaches that utilize bootstrapping to identify statistical significance on the basis of some defined criterion. Three studies are presented in the chapter that serves to showcase the issue of multiple hypothesis testing from a practical perspective for both academics and industry participants alike. The first study is the work of Cummins analysing the interactions between the energy and emissions markets that serves in part to establish how integrated the markets have become in recent years. The second study is the work of Cummins, which looks specifically at market interactions within the European Union Emissions Trading Scheme (EU ETS). The third study is the recent work of Cummins and Bucca, which looks at quantitative spread trading in the crude oil and refined products markets.