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Do Jumps Matter for Volatility Forecasting? Evidence from Energy Markets

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Cited by:

  1. Gong, Xu & Lin, Boqiang, 2018. "The incremental information content of investor fear gauge for volatility forecasting in the crude oil futures market," Energy Economics, Elsevier, vol. 74(C), pages 370-386.
  2. Matteo Bonato & Konstantinos Gkillas & Rangan Gupta & Christian Pierdzioch, 2020. "Investor Happiness and Predictability of the Realized Volatility of Oil Price," Sustainability, MDPI, vol. 12(10), pages 1-11, May.
  3. Asai, Manabu & Gupta, Rangan & McAleer, Michael, 2020. "Forecasting volatility and co-volatility of crude oil and gold futures: Effects of leverage, jumps, spillovers, and geopolitical risks," International Journal of Forecasting, Elsevier, vol. 36(3), pages 933-948.
  4. Manabu Asai & Rangan Gupta & Michael McAleer, 2019. "The Impact of Jumps and Leverage in Forecasting the Co-Volatility of Oil and Gold Futures," Energies, MDPI, vol. 12(17), pages 1-17, September.
  5. Kuruppuarachchi, Duminda & Premachandra, I.M. & Roberts, Helen, 2019. "A novel market efficiency index for energy futures and their term structure risk premiums," Energy Economics, Elsevier, vol. 77(C), pages 23-33.
  6. Dehua Shen & Andrew Urquhart & Pengfei Wang, 2020. "Forecasting the volatility of Bitcoin: The importance of jumps and structural breaks," European Financial Management, European Financial Management Association, vol. 26(5), pages 1294-1323, November.
  7. Özbekler, Ali Gencay & Kontonikas, Alexandros & Triantafyllou, Athanasios, 2021. "Volatility forecasting in European government bond markets," International Journal of Forecasting, Elsevier, vol. 37(4), pages 1691-1709.
  8. Chatziantoniou, Ioannis & Degiannakis, Stavros & Filis, George, 2019. "Futures-based forecasts: How useful are they for oil price volatility forecasting?," Energy Economics, Elsevier, vol. 81(C), pages 639-649.
  9. Stavros Degiannakis, George Filis, and Vipin Arora, 2018. "Oil Prices and Stock Markets: A Review of the Theory and Empirical Evidence," The Energy Journal, International Association for Energy Economics, vol. 0(Number 5).
  10. Li, Xiafei & Liao, Yin & Lu, Xinjie & Ma, Feng, 2022. "An oil futures volatility forecast perspective on the selection of high-frequency jump tests," Energy Economics, Elsevier, vol. 116(C).
  11. Wu, Hanlin & Li, Pan & Cao, Jiawei & Xu, Zijian, 2024. "Forecasting the Chinese crude oil futures volatility using jump intensity and Markov-regime switching model," Energy Economics, Elsevier, vol. 134(C).
  12. Nguyen, Duc Binh Benno & Prokopczuk, Marcel, 2019. "Jumps in commodity markets," Journal of Commodity Markets, Elsevier, vol. 13(C), pages 55-70.
  13. Lyócsa, Štefan & Molnár, Peter & Todorova, Neda, 2017. "Volatility forecasting of non-ferrous metal futures: Covariances, covariates or combinations?," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 51(C), pages 228-247.
  14. Qiao, Gaoxiu & Teng, Yuxin & Li, Weiping & Liu, Wenwen, 2019. "Improving volatility forecasting based on Chinese volatility index information: Evidence from CSI 300 index and futures markets," The North American Journal of Economics and Finance, Elsevier, vol. 49(C), pages 133-151.
  15. Jiawen Luo & Tony Klein & Thomas Walther & Qiang Ji, 2024. "Forecasting realized volatility of crude oil futures prices based on machine learning," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 43(5), pages 1422-1446, August.
  16. Yusui Tang & Feng Ma & Yaojie Zhang & Yu Wei, 2022. "Forecasting the oil price realized volatility: A multivariate heterogeneous autoregressive model," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(4), pages 4770-4783, October.
  17. Davide De Gaetano, 2018. "Forecast Combinations in the Presence of Structural Breaks: Evidence from U.S. Equity Markets," Mathematics, MDPI, vol. 6(3), pages 1-19, March.
  18. Liu, Jing & Ma, Feng & Yang, Ke & Zhang, Yaojie, 2018. "Forecasting the oil futures price volatility: Large jumps and small jumps," Energy Economics, Elsevier, vol. 72(C), pages 321-330.
  19. Riza Demirer & Konstantinos Gkillas & Rangan Gupta & Christian Pierdzioch, 2022. "Risk aversion and the predictability of crude oil market volatility: A forecasting experiment with random forests," Journal of the Operational Research Society, Taylor & Francis Journals, vol. 73(8), pages 1755-1767, August.
  20. Marfatia, Hardik A. & Gupta, Rangan & Cakan, Esin, 2021. "Dynamic impact of the U.S. monetary policy on oil market returns and volatility," The Quarterly Review of Economics and Finance, Elsevier, vol. 80(C), pages 159-169.
  21. 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).
  22. Luo, Jiawen & Ji, Qiang & Klein, Tony & Todorova, Neda & Zhang, Dayong, 2020. "On realized volatility of crude oil futures markets: Forecasting with exogenous predictors under structural breaks," Energy Economics, Elsevier, vol. 89(C).
  23. Lyócsa, Štefan & Todorova, Neda & Výrost, Tomáš, 2021. "Predicting risk in energy markets: Low-frequency data still matter," Applied Energy, Elsevier, vol. 282(PA).
  24. Maki, Daiki, 2024. "Forecasting downside and upside realized volatility: The role of asymmetric information," The Journal of Economic Asymmetries, Elsevier, vol. 29(C).
  25. 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).
  26. Buncic, Daniel & Gisler, Katja I.M., 2016. "Global equity market volatility spillovers: A broader role for the United States," International Journal of Forecasting, Elsevier, vol. 32(4), pages 1317-1339.
  27. Dudley Gilder & Leonidas Tsiaras, 2020. "Volatility forecasts embedded in the prices of crude‐oil options," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 40(7), pages 1127-1159, July.
  28. Degiannakis, Stavros, 2017. "The one-trading-day-ahead forecast errors of intra-day realized volatility," Research in International Business and Finance, Elsevier, vol. 42(C), pages 1298-1314.
  29. Dicle, Mehmet F. & Levendis, John, 2020. "Historic risk and implied volatility," Global Finance Journal, Elsevier, vol. 45(C).
  30. Xu Gong & Boqiang Lin, 2018. "Structural breaks and volatility forecasting in the copper futures market," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 38(3), pages 290-339, March.
  31. Dimos S. Kambouroudis & David G. McMillan & Katerina Tsakou, 2021. "Forecasting realized volatility: The role of implied volatility, leverage effect, overnight returns, and volatility of realized volatility," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 41(10), pages 1618-1639, October.
  32. Maki, Daiki & Ota, Yasushi, 2021. "Impacts of asymmetry on forecasting realized volatility in Japanese stock markets," Economic Modelling, Elsevier, vol. 101(C).
  33. Rice, Gregory & Wirjanto, Tony & Zhao, Yuqian, 2023. "Exploring volatility of crude oil intraday return curves: A functional GARCH-X model," Journal of Commodity Markets, Elsevier, vol. 32(C).
  34. Panagiotis Delis & Stavros Degiannakis & Konstantinos Giannopoulos, 2023. "What Should be Taken into Consideration when Forecasting Oil Implied Volatility Index?," The Energy Journal, , vol. 44(5), pages 231-250, September.
  35. Zhang, Yaojie & He, Mengxi & Wang, Yudong & Liang, Chao, 2023. "Global economic policy uncertainty aligned: An informative predictor for crude oil market volatility," International Journal of Forecasting, Elsevier, vol. 39(3), pages 1318-1332.
  36. Zhang, Hongwei & Zhao, Xinyi & Gao, Wang & Niu, Zibo, 2023. "The role of higher moments in predicting China's oil futures volatility: Evidence from machine learning models," Journal of Commodity Markets, Elsevier, vol. 32(C).
  37. Bu, Ruijun & Hizmeri, Rodrigo & Izzeldin, Marwan & Murphy, Anthony & Tsionas, Mike, 2023. "The contribution of jump signs and activity to forecasting stock price volatility," Journal of Empirical Finance, Elsevier, vol. 70(C), pages 144-164.
  38. Hu, Zhihao & Yang, Ben-Zhang & He, Xin-Jiang & Yue, Jia, 2024. "Equilibrium pricing of European crude oil options with stochastic behaviour and jump risks," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 219(C), pages 212-230.
  39. Song, Yuping & Huang, Jiefei & Zhang, Qichao & Xu, Yang, 2024. "Heterogeneity effect of positive and negative jumps on the realized volatility: Evidence from China," Economic Modelling, Elsevier, vol. 136(C).
  40. Liang, Chao & Tang, Linchun & Li, Yan & Wei, Yu, 2020. "Which sentiment index is more informative to forecast stock market volatility? Evidence from China," International Review of Financial Analysis, Elsevier, vol. 71(C).
  41. Buncic, Daniel & Müller, Oliver, 2017. "Measuring the output gap in Switzerland with linear opinion pools," Economic Modelling, Elsevier, vol. 64(C), pages 153-171.
  42. Degiannakis, Stavros & Filis, George, 2017. "Forecasting oil price realized volatility using information channels from other asset classes," Journal of International Money and Finance, Elsevier, vol. 76(C), pages 28-49.
  43. Hui Qu & Tianyang Wang & Peng Shangguan & Mengying He, 2024. "Revisiting the puzzle of jumps in volatility forecasting: The new insights of high‐frequency jump intensity," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 44(2), pages 218-251, February.
  44. Lyócsa, Štefan & Todorova, Neda, 2021. "What drives volatility of the U.S. oil and gas firms?," Energy Economics, Elsevier, vol. 100(C).
  45. Klein, Tony & Todorova, Neda, 2021. "Night trading with futures in China: The case of Aluminum and Copper," Resources Policy, Elsevier, vol. 73(C).
  46. Yaojie Zhang & Yudong Wang & Feng Ma & Yu Wei, 2022. "To jump or not to jump: momentum of jumps in crude oil price volatility prediction," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 8(1), pages 1-31, December.
  47. Bonato, Matteo & Gupta, Rangan & Lau, Chi Keung Marco & Wang, Shixuan, 2020. "Moments-based spillovers across gold and oil markets," Energy Economics, Elsevier, vol. 89(C).
  48. Haugom, Erik & Ray, Rina, 2017. "Heterogeneous traders, liquidity, and volatility in crude oil futures market," Journal of Commodity Markets, Elsevier, vol. 5(C), pages 36-49.
  49. Bissoondoyal-Bheenick, Emawtee & Brooks, Robert & Do, Hung Xuan & Smyth, Russell, 2020. "Exploiting the heteroskedasticity in measurement error to improve volatility predictions in oil and biofuel feedstock markets," Energy Economics, Elsevier, vol. 86(C).
  50. Qianjie Geng & Xianfeng Hao & Yudong Wang, 2024. "Forecasting the volatility of crude oil futures: A time‐dependent weighted least squares with regularization constraint," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 43(2), pages 309-325, March.
  51. Toan Luu Duc Huynh & Muhammad Shahbaz & Muhammad Ali Nasir & Subhan Ullah, 2022. "Financial modelling, risk management of energy instruments and the role of cryptocurrencies," Annals of Operations Research, Springer, vol. 313(1), pages 47-75, June.
  52. Gongyue Jiang & Gaoxiu Qiao & Feng Ma & Lu Wang, 2022. "Directly pricing VIX futures with observable dynamic jumps based on high‐frequency VIX," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 42(8), pages 1518-1548, August.
  53. Degiannakis, Stavros & Filis, George, 2016. "Forecasting oil price realized volatility: A new approach," MPRA Paper 69105, University Library of Munich, Germany.
  54. Libo Yin, 2022. "The role of intermediary capital risk in predicting oil volatility," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(1), pages 401-416, January.
  55. Lu, Xinjie & Ma, Feng & Xu, Jin & Zhang, Zehui, 2022. "Oil futures volatility predictability: New evidence based on machine learning models11All the authors contribute to the paper equally," International Review of Financial Analysis, Elsevier, vol. 83(C).
  56. Chatziantoniou, Ioannis & Filippidis, Michail & Filis, George & Gabauer, David, 2021. "A closer look into the global determinants of oil price volatility," Energy Economics, Elsevier, vol. 95(C).
  57. Jawadi, Fredj & Bourghelle, David & Rozin, Philippe & Cheffou, Abdoulkarim Idi & Uddin, Gazi Salah, 2024. "Sentiment and energy price volatility: A nonlinear high frequency analysis," Energy Economics, Elsevier, vol. 133(C).
  58. Alfeus, Mesias & Nikitopoulos, Christina Sklibosios, 2022. "Forecasting volatility in commodity markets with long-memory models," Journal of Commodity Markets, Elsevier, vol. 28(C).
  59. Degiannakis, Stavros, 2018. "Multiple days ahead realized volatility forecasting: Single, combined and average forecasts," Global Finance Journal, Elsevier, vol. 36(C), pages 41-61.
  60. Jiqian Wang & Feng Ma & M.I.M. Wahab & Dengshi Huang, 2021. "Forecasting China's Crude Oil Futures Volatility: The Role of the Jump, Jumps Intensity, and Leverage Effect," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(5), pages 921-941, August.
  61. Chen, Wang & Ma, Feng & Wei, Yu & Liu, Jing, 2020. "Forecasting oil price volatility using high-frequency data: New evidence," International Review of Economics & Finance, Elsevier, vol. 66(C), pages 1-12.
  62. Buncic, Daniel & Gisler, Katja I.M., 2017. "The role of jumps and leverage in forecasting volatility in international equity markets," Journal of International Money and Finance, Elsevier, vol. 79(C), pages 1-19.
  63. Ignatieva, Katja & Wong, Patrick, 2022. "Modelling high frequency crude oil dynamics using affine and non-affine jump–diffusion models," Energy Economics, Elsevier, vol. 108(C).
  64. Degiannakis, Stavros & Filis, George, 2022. "Oil price volatility forecasts: What do investors need to know?," Journal of International Money and Finance, Elsevier, vol. 123(C).
  65. Guo, Xiaozhu & Huang, Yisu & Liang, Chao & Umar, Muhammad, 2022. "Forecasting volatility of EUA futures: New evidence," Energy Economics, Elsevier, vol. 110(C).
  66. Yuqing Feng & Yaojie Zhang & Yudong Wang, 2024. "Out‐of‐sample volatility prediction: Rolling window, expanding window, or both?," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 43(3), pages 567-582, April.
  67. Qu, Hui & Li, Guo, 2023. "Multi-perspective investor attention and oil futures volatility forecasting," Energy Economics, Elsevier, vol. 119(C).
  68. Xu Gong & Boqiang Lin, 2022. "Predicting the volatility of crude oil futures: The roles of leverage effects and structural changes," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(1), pages 610-640, January.
  69. Daiki Maki & Yasushi Ota, 2020. "The impacts of asymmetry on modeling and forecasting realized volatility in Japanese stock markets," Papers 2006.00158, arXiv.org.
  70. Lu, Botao & Ma, Feng & Wang, Jiqian & Ding, Hui & Wahab, M.I.M., 2021. "Harnessing the decomposed realized measures for volatility forecasting: Evidence from the US stock market," International Review of Economics & Finance, Elsevier, vol. 72(C), pages 672-689.
  71. Ma, Feng & Wahab, M.I.M. & Huang, Dengshi & Xu, Weiju, 2017. "Forecasting the realized volatility of the oil futures market: A regime switching approach," Energy Economics, Elsevier, vol. 67(C), pages 136-145.
  72. Bonnier, Jean-Baptiste, 2022. "Forecasting crude oil volatility with exogenous predictors: As good as it GETS?," Energy Economics, Elsevier, vol. 111(C).
  73. Maki, Daiki, 2024. "Asymmetric effect of trading volume on realized volatility," International Review of Economics & Finance, Elsevier, vol. 94(C).
  74. Ma, Feng & Zhang, Yaojie & Huang, Dengshi & Lai, Xiaodong, 2018. "Forecasting oil futures price volatility: New evidence from realized range-based volatility," Energy Economics, Elsevier, vol. 75(C), pages 400-409.
  75. Chen, Yixiang & Ma, Feng & Zhang, Yaojie, 2019. "Good, bad cojumps and volatility forecasting: New evidence from crude oil and the U.S. stock markets," Energy Economics, Elsevier, vol. 81(C), pages 52-62.
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