IDEAS home Printed from https://ideas.repec.org/r/eee/eneeco/v56y2016icp64-74.html

Asymmetric impacts of fundamentals on the natural gas futures volatility: An augmented GARCH approach

Citations

Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
as


Cited by:

  1. Christian Urom & Gideon Ndubuisi & Jude Ozor, 2021. "Economic activity, and financial and commodity markets’ shocks: An analysis of implied volatility indexes," International Economics, CEPII research center, issue 165, pages 51-66.
  2. Hailemariam, Abebe & Smyth, Russell, 2019. "What drives volatility in natural gas prices?," Energy Economics, Elsevier, vol. 80(C), pages 731-742.
  3. Dimitrios I. Vortelinos & Konstantinos Gkillas, 2018. "Intraday realised volatility forecasting and announcements," International Journal of Banking, Accounting and Finance, Inderscience Enterprises Ltd, vol. 9(1), pages 88-118.
  4. Sherzod N. Tashpulatov, 2022. "Modeling Electricity Price Dynamics Using Flexible Distributions," Mathematics, MDPI, vol. 10(10), pages 1-15, May.
  5. Liang, Chao & Xia, Zhenglan & Lai, Xiaodong & Wang, Lu, 2022. "Natural gas volatility prediction: Fresh evidence from extreme weather and extended GARCH-MIDAS-ES model," Energy Economics, Elsevier, vol. 116(C).
  6. Luo, Keyu & Guo, Qiang & Li, Xiafei, 2022. "Can the return connectedness indices from grey energy to natural gas help to forecast the natural gas returns?," Energy Economics, Elsevier, vol. 109(C).
  7. Gong, Xue & Lai, Ping & He, Mengxi & Wen, Danyan, 2024. "Climate risk and energy futures high frequency volatility prediction," Energy, Elsevier, vol. 307(C).
  8. Khalfaoui, Rabeh & Goodell, John W. & Mefteh-Wali, Salma & Chishti, Muhammad Zubair & Gozgor, Giray, 2024. "Impact of climate risk shocks on global food and agricultural markets: A multiscale and tail connectedness analysis," International Review of Financial Analysis, Elsevier, vol. 93(C).
  9. Huang, Zhouchun & Zheng, Qipeng Phil, 2020. "A multistage stochastic programming approach for preventive maintenance scheduling of GENCOs with natural gas contract," European Journal of Operational Research, Elsevier, vol. 287(3), pages 1036-1051.
  10. Chao Liang & Feng Ma & Lu Wang & Qing Zeng, 2021. "The information content of uncertainty indices for natural gas futures volatility forecasting," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(7), pages 1310-1324, November.
  11. Wang, Lu & Wang, Xing & Liang, Chao, 2024. "Natural gas volatility prediction via a novel combination of GARCH-MIDAS and one-class SVM," The Quarterly Review of Economics and Finance, Elsevier, vol. 98(C).
  12. Gong, Xue & Ye, Xin & Zhang, Weiguo & Zhang, Yue, 2023. "Predicting energy futures high-frequency volatility using technical indicators: The role of interaction," Energy Economics, Elsevier, vol. 119(C).
  13. Kshitij Sharma & Yogesh K. Dwivedi & Bhimaraya Metri, 2024. "Incorporating causality in energy consumption forecasting using deep neural networks," Annals of Operations Research, Springer, vol. 339(1), pages 537-572, August.
  14. Zhuolin Wu & Jiaqi Zhou & Xiaobing Yu, 2025. "Forecast Natural Gas Price by an Extreme Learning Machine Framework Based on Multi-Strategy Grey Wolf Optimizer and Signal Decomposition," Sustainability, MDPI, vol. 17(12), pages 1-37, June.
  15. Kannika Duangnate & James W. Mjelde, 2020. "Prequential forecasting in the presence of structure breaks in natural gas spot markets," Empirical Economics, Springer, vol. 59(5), pages 2363-2384, November.
  16. Josef Novotny & Petr Hajek, 2026. "A hybrid adaptive trading strategy integrating investor sentiment for precious metal ETFs," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 12(1), pages 1-33, December.
  17. Urom, Christian & Ndubuisi, Gideon & Ozor, Jude, 2021. "Economic activity, and financial and commodity markets’ shocks: An analysis of implied volatility indexes," International Economics, Elsevier, vol. 165(C), pages 51-66.
  18. Sherzod N. Tashpulatov, 2021. "Modeling and Estimating Volatility of Day-Ahead Electricity Prices," Mathematics, MDPI, vol. 9(7), pages 1-11, March.
  19. Dai, Peng-Fei & Xiong, Xiong & Zhang, Jin & Zhou, Wei-Xing, 2022. "The role of global economic policy uncertainty in predicting crude oil futures volatility: Evidence from a two-factor GARCH-MIDAS model," Resources Policy, Elsevier, vol. 78(C).
  20. Urom, Christian & Ndubuisi, Gideon & Guesmi, Khaled, 2022. "How do financial and commodity markets volatility react to real economic activity?," Finance Research Letters, Elsevier, vol. 47(PB).
  21. Yanting Chen & Peter R. Hartley & Yihui Lan, 2023. "Temperature, storage, and natural gas futures prices," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 43(4), pages 549-575, April.
  22. Horváth, Roman & Kalistová, Anna & Lyócsa, Štefan & Miškufová, Marta & Moravcová, Michala, 2025. "Do hurricanes cause storm on the stock market? The case of US energy companies," International Review of Financial Analysis, Elsevier, vol. 97(C).
  23. Chang, Chia-Lin & McAleer, Michael & Wang, Yanghuiting, 2018. "Testing Co-Volatility spillovers for natural gas spot, futures and ETF spot using dynamic conditional covariances," Energy, Elsevier, vol. 151(C), pages 984-997.
  24. Zhang, Yu & Yu, Xin & Zhang, Peng & Zhang, Haoran, 2025. "Price impacts of natural gas chokepoints on China: an energy security analysis of the Russia-Ukraine conflict," Utilities Policy, Elsevier, vol. 96(C).
  25. Monteux, Manou & Arcuri, Maria Cristina & Gandolfi, Gino & Caselli, Stefano, 2025. "Can extreme weather forecasts lead to a risk premium? Evidence of a non-linear response in U.S. natural gas futures," The North American Journal of Economics and Finance, Elsevier, vol. 80(C).
  26. Pham, Son Duy & Nguyen, Thao Thac Thanh & Do, Hung Xuan, 2023. "Natural gas and the utility sector nexus in the U.S.: Quantile connectedness and portfolio implications," Energy Economics, Elsevier, vol. 120(C).
  27. Sherzod N. Tashpulatov, 2021. "The Impact of Regulatory Reforms on Demand Weighted Average Prices," Mathematics, MDPI, vol. 9(10), pages 1-15, May.
IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.