Forecasting the European carbon market

Summary. In an effort to meet its obligations under the Kyoto Protocol, the European Union has introduced a cap‐and‐trade scheme where mandated companies are allocated permits to emit carbon dioxide. Financial markets have developed that allow companies to trade these carbon permits. Several recent studies have attempted to model their prices. There are many institutional features that potentially impact on carbon prices and associated financial futures, making such an undertaking quite different from modelling conventional financial assets traded in mature markets. We forecast the carbon markets by using dynamic model averaging, which is a recently developed statistical method which has three advantages over conventional approaches. First, it allows the coefficients on the predictors in a forecasting model to change over time. Second, it allows for the entire forecasting model to change over time. Third, it surmounts statistical problems which arise from the large number of potential predictors that can explain carbon prices. Our empirical results indicate that there are both important policy and statistical benefits with our approach. Statistically, we present strong evidence that there is substantial turbulence and change in the carbon markets. We find that dynamic model averaging can model these features and forecast accurately compared with conventional approaches.