Forecast of long‐term EUA price probability using momentum strategy and GBM simulation

Abstract

CO2 storage projects are financially intensive and, without the European Union emission trading scheme that encourages CO2 emission reduction projects, they will not be cost effective, that is, feasible. Similar to the huge uncertainties involved in long‐term energy price prediction, CO2 market price is volatile. In this paper, indicators for key CO2 price changes are detected by moving average analysis. To prove the validity of the methods, geometric Brownian motion (GBM) simulations were performed for different drift and volatility values. Drift, the standard deviation of CO2 price changes and CO2 volatility were used on a daily, weekly and monthly basis for short term simulations and on a weekly basis for long term simulations. GBM simulation can help determine the probability of a European emission allowances (EUA) price, which is featured by great variations, depending on the period. Signals for periods were determined by momentum strategy, with 60 days for short and 365 days for the long moving average. They show correlation with natural gas prices, that is, EUA signals appear 13–17 months after the signal in natural gas price. Among the vast number of proposed hybrid prediction models, this correlation allows the prediction of a long‐term price trend. It seems that back‐loading measures obstructed risk estimates because they resulted in extreme price drift in some periods, as the consequence of rebalancing in supply and demand. © 2020 Society of Chemical Industry and John Wiley & Sons, Ltd.