Journal of Energy Markets

Forecasting of carbon emissions prices by the adaptive neuro–fuzzy inference system

G. Atsalakis, D. Frantzis and C. Zopounidis


The need for accurate forecasts has increased in recent years but there has as yet been limited research on carbon emissions price trends. This study uses the adaptive neuro-fuzzy inference system (ANFIS) model to forecast the price trends of carbon emissions: ANFIS is a hybrid system consisting of neural networks and fuzzy logic. It uses a combination of the least-squares method and the back-propagation gradient descent method to estimate the optimal carbon price forecast parameters. Although the system is well known, it has been modified in order to best process the carbon emissions data sets. We used daily data sets covering the period from October 14, 2009 to October 29, 2013, using 1074 observations to train and evaluate the model. The results of the simulation and experimental investigations carried out in the laboratory showed that the model is suitable for forecasting carbon emissions price trends. A further evaluation compared the returns from trading actions, according to the signal of the forecasted system, with the buy-and-hold strategy.

Sorry, our subscription options are not loading right now

Please try again later. Get in touch with our customer services team if this issue persists.

New to View our subscription options

You need to sign in to use this feature. If you don’t have a account, please register for a trial.

Sign in
You are currently on corporate access.

To use this feature you will need an individual account. If you have one already please sign in.

Sign in.

Alternatively you can request an individual account here