Modeling the determinants of CO2 emission allowance prices in the EU ETS under uncertainty

The dataset was created as part of the grant project titled "Modeling the determinants of CO2 emission allowance prices in the EU ETS under uncertainty". The project was funded by the National Science Centre under grant number 2021/05/X/ST6/01693.The data includes:Results of EUA price prediction using a combination of Principal Component Analysis (PCA) and various supervised machine learning methods.MATLAB script files for analyzing carbon price prediction with different feature selection methods (F-test, Neighborhood Component Feature Selection method, RreliefF).Excel files containing elements for the Hellwig method to determine an optimal set of carbon price determinants.The full model with ordered fuzzy numbers for EUA price.Due to the terms of the subscription agreement for EU ETS market online, the source data will not be made available.The scope of the research is described in related publications: Short-term modeling of carbon price based on fuel and energy determinants in EU ETS https://doi.org/10.1016/j.jclepro.2023.137970. Forecasting day-ahead carbon price by modelling its determinants using the PCA-based approach https://doi.org/10.3390/en15218057.Please see readme.txt file attached for more information.