TY - JOUR
T1 - Machine learning in energy economics and finance
T2 - A review
AU - Ghoddusi, Hamed
AU - Creamer, Germán G.
AU - Rafizadeh, Nima
N1 - Publisher Copyright:
© 2019 Elsevier B.V.
PY - 2019/6
Y1 - 2019/6
N2 - Machine learning (ML) is generating new opportunities for innovative research in energy economics and finance. We critically review the burgeoning literature dedicated to Energy Economics/Finance applications of ML. Our review identifies applications in areas such as predicting energy prices (e.g. crude oil, natural gas, and power), demand forecasting, risk management, trading strategies, data processing, and analyzing macro/energy trends. We critically review the content (methods and findings) of more than 130 articles published between 2005 and 2018. Our analysis suggests that Support Vector Machine (SVM), Artificial Neural Network (ANN), and Genetic Algorithms (GAs) are among the most popular techniques used in energy economics papers. We discuss the achievements and limitations of existing literature. The survey concludes by identifying current gaps and offering some suggestions for future research.
AB - Machine learning (ML) is generating new opportunities for innovative research in energy economics and finance. We critically review the burgeoning literature dedicated to Energy Economics/Finance applications of ML. Our review identifies applications in areas such as predicting energy prices (e.g. crude oil, natural gas, and power), demand forecasting, risk management, trading strategies, data processing, and analyzing macro/energy trends. We critically review the content (methods and findings) of more than 130 articles published between 2005 and 2018. Our analysis suggests that Support Vector Machine (SVM), Artificial Neural Network (ANN), and Genetic Algorithms (GAs) are among the most popular techniques used in energy economics papers. We discuss the achievements and limitations of existing literature. The survey concludes by identifying current gaps and offering some suggestions for future research.
KW - Artificial Neural Network
KW - Crude oil
KW - Electricity price
KW - Energy finance
KW - Energy markets
KW - Forecasting
KW - Machine learning
KW - Support Vector Machine
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U2 - 10.1016/j.eneco.2019.05.006
DO - 10.1016/j.eneco.2019.05.006
M3 - Article
AN - SCOPUS:85066428783
SN - 0140-9883
VL - 81
SP - 709
EP - 727
JO - Energy Economics
JF - Energy Economics
ER -