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Examining connections between the fourth industrial revolution and energy markets

Elsayed, Ahmed; Syed Mabruk Billah; Goodell, John W.; … - In: Energy economics 133 (2024), pp. 1-20

We investigate the relationship between assets related to the fourth industrial revolution and alternatively dirty and clean energy markets. We examine portfolio diversification benefits and risk reduction gains based on three portfolio construction techniques. Results of static connectedness...

Persistent link: https://www.econbiz.de/10015049528

Machine learning and oil price point and density forecasting

Costa, Alexandre Bonnet R.; Ferreira, Pedro Cavalcanti; … - In: Energy economics 102 (2021), pp. 1-21

Persistent link: https://www.econbiz.de/10013162181

Predicting energy poverty with combinations of remote-sensing and socioeconomic survey data in India : evidence from machine learning

Wang, Hanjie; Maruejols, Lucie; Yu, Xiaohua - In: Energy economics 102 (2021), pp. 1-13

Persistent link: https://www.econbiz.de/10013162202

Predicting corporate carbon footprints for climate finance risk analyses : a machine learning approach

Nguyen, Quyen; Diaz-Rainey, Ivan; Kuruppuarachchi, Duminda - In: Energy economics 95 (2021), pp. 1-18

Persistent link: https://www.econbiz.de/10012816864

Won't get fooled again : a supervised machine learning approach for screening gasoline cartels

Silveira, Douglas; Vasconcelos, Silvinha Pinto; … - In: Energy economics 105 (2022), pp. 1-18

Persistent link: https://www.econbiz.de/10013201809

Machine learning in energy economics and finance: a review

Ghoddusi, Hamed; Creamer Guillén, Germán; Rafizadeh, Nima - In: Energy economics 81 (2019), pp. 709-727

Persistent link: https://www.econbiz.de/10012172954

Using machine learning tools for forecasting natural gas consumption in the province of Istanbul

Beyca, Ömer Faruk; Ervural, Beyzanur Cayir; Tatoğlu, Ekrem - In: Energy economics 80 (2019), pp. 937-949

Persistent link: https://www.econbiz.de/10012173755

Toward high-resolution projection of electricity prices : a machine learning approach to quantifying the effects of high fuel and CO2 prices

Madadkhani, Shiva; Ikonnikova, Svetlana - In: Energy economics 129 (2024), pp. 1-18

Persistent link: https://www.econbiz.de/10014558952

Forecasting the realized variance of oil-price returns using machine learning : is there a role for U.S. state-level uncertainty?

Çepni, Oğuzhan; Gupta, Rangan; Pienaar, Daniel; … - In: Energy economics 114 (2022), pp. 1-14

Persistent link: https://www.econbiz.de/10013477404

Using machine learning to model technological heterogeneity in carbon emission efficiency evaluation : the case of China's cities

Wang, Ailun; Hu, Shuo; Li, Jianglong - In: Energy economics 114 (2022), pp. 1-15

Persistent link: https://www.econbiz.de/10013477406