The aim of this paper is to identify the fundamental factors that drive the allowances market and to built an APT-like model in order to provide accurate forecasts for CO2. We show that historic 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 provides with the best fit results. Introducing dynamics inside the parameters of the APT model via a Hidden Markov Chain Model outperforms the results obtained with a static approach. Empirical results clearly indicate that this model could be used for price forecasting, that it is effective in and out of sample producing consisten results in allowances futures price prediction.