Energy Forecasting

Inbunden, Engelska, 2025

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The different contributions comprehensively forecast a wide range of energy, including crude oil, coal, natural gas, electricity, renewable energy, and nuclear energy, and further explore the application of energy information in the fields of economic and financial forecasting.

Produktinformation

Utgivningsdatum2025-08-12
Mått155 x 235 x 22 mm
Vikt621 g
FormatInbunden
SpråkEngelska
SerieClimate Change and Energy Transition
Antal sidor297
FörlagSpringer Nature Switzerland AG
ISBN9789819676545

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Yudong Wang is a Professor at the School of Economics and Management, Nanjing University of Science and Technology. He is interested in the area of energy finance and financial forecasting. He has published more than 100 papers in financial and forecasting journals including Management Science, Journal of Financial Markets, Journal of Banking and Finance. He is an Associate Editor for Journal of Forecasting. He is selected as 2019-2021 Elsevier “Chinese highly cited scholar”.Yaojie Zhang is an Associate Professor at the School of Economics and Management, Nanjing University of Science and Technology. His research interests include financial forecasting and energy finance. He has published more than 80 papers in the Journal of Empirical Finance, International Journal of Forecasting, Energy Economics, and many others. He is an Associate Editor for Bulletin of Economic Research and a Young Editorial Board Member for China Finance Review International.

Chapter 1. Forecasting crude oil prices.- Chapter 2. Forecasting coal prices.- Chapter 3. Forecasting natural gas prices.- Chapter 4. Forecasting electricity prices.- Chapter 5. Forecasting renewable and nuclear energy.- Chapter 6. Forecasting Chinese oil futures market.- Chapter 7. Forecasting energy production and consumption.- Chapter 8. Forecasting energy market volatility.- Chapter 9. Energy and economic forecasting.- Chapter 10. Energy information and stock return predictability.- Chapter 11. Energy information and exchange rate forecasting.- Chapter 12. Climate risk and energy price forecasting.- Chapter 13. Machine learning and energy forecasting.- Chapter 14. Big data and energy forecasting.- Etc.