Abstract:

The aim of this paper is to identify the fundamental factors that drive the allowances market and to build an APT-like model in order to provide accurate price forecasts for CO2. We show that historical dependency patterns emphasis energy, natural gas, oil, coal and equity indexes as major factors driving the carbon allowances prices. There is strong evidence that model residuals are heavily tailed and asymmetric, thereby generalized hyperbolic distribution providing with the best fit results. Introducing dynamics inside the parameters of APT model via hidden Markov Chain outperforms the forecasting results obtained with a static approach.