“Modelling and Predicting Energy Time Series: A Comparison of Econometric Models and Machine Learning Techniques”

Modelling and predicting energy time series using econometric models and machine learning
techniques
Since the covid – 19 era and the war in Ukraine, the energy sector has attracted the interest of many researchers and
practitioners. The aim of this thesis is to develop statistical/ econometric models and machine learning techniques to
predict the price of energy time series or their percentage changes.
References
Weron, R. (2014) Electricity price forecasting: A review of the state-of-the-art with a look into the future,
International Journal of Forecasting, 30, 1030-1081.
Ghoddusi, H., Creamer, G., and Rafizadeh, N. (2019), Machine learning in energy economics and finance: A review,
Energy Economics, 81, 709–727