JOURNAL: Forecasting carbon prices: A literature review
Summary
Authors:
Konstantinos Bisiotis
Dimitris Christopoulos
George Tzougas
Heriot-Watt University
Forecasting carbon prices: A literature review
Journal of Forecasting
October 2025
This paper explores recent progress in forecasting carbon prices, a key factor in tackling climate change through emissions trading systems. It reviews and compares a range of prediction methods, from traditional time series and econometric models to newer machine learning techniques such as neural networks and Long Short-Term Memory (LSTM) models. The study highlights how advanced machine learning approaches can better capture complex and changing market patterns. It also considers emerging hybrid models that combine different methods to improve the accuracy of both short- and long-term carbon price forecasts, supporting more effective climate and investment decisions.
Associated Research
IDRIC – MIP 3.6 Opportunities in financing the green transition