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Energy Forecasting [Kõva köide]

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  • Formaat: Hardback, 417 pages, kõrgus x laius: 235x155 mm, 40 Illustrations, color; 3 Illustrations, black and white; VI, 417 p. 43 illus., 40 illus. in color., 1 Hardback
  • Sari: Climate Change and Energy Transition
  • Ilmumisaeg: 12-Oct-2025
  • Kirjastus: Springer Nature Switzerland AG
  • ISBN-10: 9819676541
  • ISBN-13: 9789819676545
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  • Formaat: Hardback, 417 pages, kõrgus x laius: 235x155 mm, 40 Illustrations, color; 3 Illustrations, black and white; VI, 417 p. 43 illus., 40 illus. in color., 1 Hardback
  • Sari: Climate Change and Energy Transition
  • Ilmumisaeg: 12-Oct-2025
  • Kirjastus: Springer Nature Switzerland AG
  • ISBN-10: 9819676541
  • ISBN-13: 9789819676545

This book focuses on the application of multiple forecasting methods to energy forecasting problems. 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. The main features of this book are: (1) providing a comprehensive overview of energy forecasting; (2) presenting a variety of energy forecasting methods; and (3) illustrating the economic origins of energy price predictability. This book serves as a professional book for graduate students in energy economics and management at various institutions of higher learning and at the same time as a reference book for teachers, researchers, and market participants in energy economics and management.  

 
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.
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.