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News, volatility and jumps: the case of natural gas futures
Citations
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Cited by:
- Broadstock, David C. & Zhang, Dayong, 2019. "Social-media and intraday stock returns: The pricing power of sentiment," Finance Research Letters, Elsevier, vol. 30(C), pages 116-123.
- David E. Allen & Michael McAleer & Abhay K. Singh, 2019.
"Daily market news sentiment and stock prices,"
Applied Economics, Taylor & Francis Journals, vol. 51(30), pages 3212-3235, June.
- David E. Allen & Michael McAleer & Abhay K. Singh, 2015. "Daily Market News Sentiment and Stock Prices," Documentos de Trabajo del ICAE 2015-11, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico.
- Allen, D.E. & McAleer, M.J. & Singh, A.K., 2015. "Daily Market News Sentiment and Stock Prices," Econometric Institute Research Papers EI2015-23, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
- David E. Allen & Michael McAleer & Abhay K. Singh, 2015. "Daily Market News Sentiment and Stock Prices," Tinbergen Institute Discussion Papers 15-090/III, Tinbergen Institute.
- Štefan Lyócsa & Peter Molnár, 2016. "Volatility forecasting of strategically linked commodity ETFs: gold-silver," Quantitative Finance, Taylor & Francis Journals, vol. 16(12), pages 1809-1822, December.
- Ahmed, Walid M.A., 2018. "On the interdependence of natural gas and stock markets under structural breaks," The Quarterly Review of Economics and Finance, Elsevier, vol. 67(C), pages 149-161.
- Akihiro Omura & Neda Todorova, 2019. "The quantile dependence of commodity futures markets on news sentiment," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 39(7), pages 818-837, July.
- Wang, Yanlong & Li, Haixia & Altuntaş, Mehmet, 2022. "Volatility in natural resources commodity prices: Evaluating volatility in oil and gas rents," Resources Policy, Elsevier, vol. 77(C).
- Besma Hkiri & Juncal Cunado & Mehmet Balcilar & Rangan Gupta, 2021.
"Time-varying relationship between conventional and unconventional monetary policies and risk aversion: international evidence from time- and frequency-domains,"
Empirical Economics, Springer, vol. 61(6), pages 2963-2983, December.
- Besma Hkiri & Juncal Cunado & Mehmet Balcilar & Rangan Gupta, 2019. "Time-Varying Relationship between Conventional and Unconventional Monetary Policies and Risk Aversion: International Evidence from Time- and Frequency-Domains," Working Papers 201965, University of Pretoria, Department of Economics.
- Gong, Xue & Lai, Ping & He, Mengxi & Wen, Danyan, 2024. "Climate risk and energy futures high frequency volatility prediction," Energy, Elsevier, vol. 307(C).
- Lyócsa, Štefan & Molnár, Peter, 2018. "Exploiting dependence: Day-ahead volatility forecasting for crude oil and natural gas exchange-traded funds," Energy, Elsevier, vol. 155(C), pages 462-473.
- Massimiliano Caporin & Francesco Poli, 2017. "Building News Measures from Textual Data and an Application to Volatility Forecasting," Econometrics, MDPI, vol. 5(3), pages 1-46, August.
- Mensi, Walid & Rehman, Mobeen Ur & Maitra, Debasish & Al-Yahyaee, Khamis Hamed & Vo, Xuan Vinh, 2021. "Oil, natural gas and BRICS stock markets: Evidence of systemic risks and co-movements in the time-frequency domain," Resources Policy, Elsevier, vol. 72(C).
- Qiu, Yue & Wang, Zongrun & Xie, Tian & Zhang, Xinyu, 2021. "Forecasting Bitcoin realized volatility by exploiting measurement error under model uncertainty," Journal of Empirical Finance, Elsevier, vol. 62(C), pages 179-201.
- Matthew F. Dixon & Cuneyt Gurcan Akcora & Yulia R. Gel & Murat Kantarcioglu, 2019. "Blockchain analytics for intraday financial risk modeling," Digital Finance, Springer, vol. 1(1), pages 67-89, November.
- 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).
- Tom Marty & Bruce Vanstone & Tobias Hahn, 2020. "News media analytics in finance: a survey," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 60(2), pages 1385-1434, June.
- M. Karanasos & S. Yfanti & A. Christopoulos, 2021. "The long memory HEAVY process: modeling and forecasting financial volatility," Annals of Operations Research, Springer, vol. 306(1), pages 111-130, November.
- Tsai, I-Chun & Chen, Han-Bo & Lin, Che-Chun, 2024. "The ability of energy commodities to hedge the dynamic risk of epidemic black swans," Resources Policy, Elsevier, vol. 89(C).
- Gkillas, Konstantinos & Bouri, Elie & Gupta, Rangan & Roubaud, David, 2022.
"Spillovers in Higher-Order Moments of Crude Oil, Gold, and Bitcoin,"
The Quarterly Review of Economics and Finance, Elsevier, vol. 84(C), pages 398-406.
- Konstantinos Gkillas & Elie Bouri & Rangan Gupta & David Roubaud, 2020. "Spillovers in Higher-Order Moments of Crude Oil, Gold, and Bitcoin," Working Papers 202068, University of Pretoria, Department of Economics.
- Jian Li & Zhenjing Xu & Huijuan Xu & Ling Tang & Lean Yu, 2017. "Forecasting Oil Price Trends with Sentiment of Online News Articles," Asia-Pacific Journal of Operational Research (APJOR), World Scientific Publishing Co. Pte. Ltd., vol. 34(02), pages 1-22, April.
- Wang, Jiqian & Ma, Feng & Bouri, Elie & Zhong, Juandan, 2022. "Volatility of clean energy and natural gas, uncertainty indices, and global economic conditions," Energy Economics, Elsevier, vol. 108(C).
- Oleksandr Castello & Marina Resta, 2023. "A Machine-Learning-Based Approach for Natural Gas Futures Curve Modeling," Energies, MDPI, vol. 16(12), pages 1-22, June.
- Stavroula Yfanti & Georgios Chortareas & Menelaos Karanasos & Emmanouil Noikokyris, 2022. "A three‐dimensional asymmetric power HEAVY model," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(3), pages 2737-2761, July.
- Dungey, Mardi & Matei, Marius & Treepongkaruna, Sirimon, 2020. "Examining stress in Asian currencies: A perspective offered by high frequency financial market data," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 67(C).
- Xu, Yongdeng, 2022. "The Exponential HEAVY Model: An Improved Approach to Volatility Modeling and Forecasting," Cardiff Economics Working Papers E2022/5, Cardiff University, Cardiff Business School, Economics Section.
- Janda, Karel & Kourilek, Jakub, 2020. "Residual shape risk on natural gas market with mixed jump diffusion price dynamics," Energy Economics, Elsevier, vol. 85(C).
- Danilo Vassallo & Giacomo Bormetti & Fabrizio Lillo, 2019. "A tale of two sentiment scales: Disentangling short-run and long-run components in multivariate sentiment dynamics," Papers 1910.01407, arXiv.org, revised Sep 2020.
- Audrino, Francesco & Tetereva, Anastasija, 2019. "Sentiment spillover effects for US and European companies," Journal of Banking & Finance, Elsevier, vol. 106(C), pages 542-567.
- Svetlana Borovkova & Evgeny Garmaev & Philip Lammers & Jordi Rustige, 2017. "SenSR: A sentiment-based systemic risk indicator," DNB Working Papers 553, Netherlands Central Bank, Research Department.
- 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).
- Audrino, Francesco & Sigrist, Fabio & Ballinari, Daniele, 2020. "The impact of sentiment and attention measures on stock market volatility," International Journal of Forecasting, Elsevier, vol. 36(2), pages 334-357.
- Guglielmo Maria Caporale & Menelaos Karanasos & Stavroula Yfanti, 2019. "Macro-Financial Linkages in the High-Frequency Domain: The Effects of Uncertainty on Realized Volatility," CESifo Working Paper Series 8000, CESifo.
- Herrera, Gabriel Paes & Constantino, Michel & Su, Jen-Je & Naranpanawa, Athula, 2022. "Renewable energy stocks forecast using Twitter investor sentiment and deep learning," Energy Economics, Elsevier, vol. 114(C).