IDEAS home Printed from https://ideas.repec.org/r/zbw/qmsrps/201910.html

Forecasting Realized Volatility of Agricultural Commodity Futures with Infinite Hidden Markov HAR Models

Citations

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


Cited by:

  1. Xu, Yan & Liu, Tianli & Du, Pei, 2024. "Volatility forecasting of crude oil futures based on Bi-LSTM-Attention model: The dynamic role of the COVID-19 pandemic and the Russian-Ukrainian conflict," Resources Policy, Elsevier, vol. 88(C).
  2. Xu, Buyun & Wu, Zhimin, 2025. "Real-time GARCH@CARR: A joint model of returns, realized measure of volatility and current intraday information," The North American Journal of Economics and Finance, Elsevier, vol. 76(C).
  3. Rangan Gupta & Christian Pierdzioch, 2024. "Multi-Task Forecasting of the Realized Volatilities of Agricultural Commodity Prices," Mathematics, MDPI, vol. 12(18), pages 1-26, September.
  4. Rui Luo & Jinpei Liu & Piao Wang & Zhifu Tao & Huayou Chen, 2024. "A multisource data‐driven combined forecasting model based on internet search keyword screening method for interval soybean futures price," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 43(2), pages 366-390, March.
  5. Li, Chenxing & Yang, Qiao, 2025. "An infinite hidden Markov model with GARCH for short-term interest rates," Finance Research Letters, Elsevier, vol. 80(C).
  6. Hu, Nan & Yin, Xuebao & Yao, Yuhang, 2025. "A novel HAR-type realized volatility forecasting model using graph neural network," International Review of Financial Analysis, Elsevier, vol. 98(C).
  7. 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.
  8. Petropoulos, Fotios & Apiletti, Daniele & Assimakopoulos, Vassilios & Babai, Mohamed Zied & Barrow, Devon K. & Ben Taieb, Souhaib & Bergmeir, Christoph & Bessa, Ricardo J. & Bijak, Jakub & Boylan, Joh, 2022. "Forecasting: theory and practice," International Journal of Forecasting, Elsevier, vol. 38(3), pages 705-871.
    • Fotios Petropoulos & Daniele Apiletti & Vassilios Assimakopoulos & Mohamed Zied Babai & Devon K. Barrow & Souhaib Ben Taieb & Christoph Bergmeir & Ricardo J. Bessa & Jakub Bijak & John E. Boylan & Jet, 2020. "Forecasting: theory and practice," Papers 2012.03854, arXiv.org, revised Jan 2022.
  9. Enilov, Martin & Mensi, Walid & Stankov, Petar, 2023. "Does safe haven exist? Tail risks of commodity markets during COVID-19 pandemic," Journal of Commodity Markets, Elsevier, vol. 29(C).
  10. Lin Wang & Wuyue An & Feng‐Ting Li, 2024. "Text‐based corn futures price forecasting using improved neural basis expansion network," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 43(6), pages 2042-2063, September.
  11. Nguyen, Hien Thi & Nguyen, Hoang & Tran, Minh-Ngoc, 2024. "Deep learning enhanced volatility modeling with covariates," Finance Research Letters, Elsevier, vol. 69(PB).
  12. Algirdas Justinas Staugaitis & Bernardas Vaznonis, 2022. "Financial Speculation Impact on Agricultural and Other Commodity Return Volatility: Implications for Sustainable Development and Food Security," Agriculture, MDPI, vol. 12(11), pages 1-27, November.
  13. Jiawen Luo & Shengjie Fu & Oguzhan Cepni & Rangan Gupta, 2025. "The Role of Uncertainty in Forecasting Realized Covariance of US State-Level Stock Returns: A Reverse-MIDAS Approach," Working Papers 202501, University of Pretoria, Department of Economics.
  14. Lyu, Yongjian & Yang, Zhidan & Luo, Ya & Qin, Zhilong & Yi, Heling & Ke, Rui, 2025. "Forecasting the volatility of crude oil futures market: Does the simple 5-minute RV hold up?," Energy Economics, Elsevier, vol. 146(C).
  15. Zhang, Yue-Jun & Zhang, Han, 2023. "Volatility forecasting of crude oil futures market: Which structural change-based HAR models have better performance?," International Review of Financial Analysis, Elsevier, vol. 85(C).
  16. Matteo Bonato & Oguzhan Cepni & Rangan Gupta & Christian Pierdzioch, 2024. "Forecasting the realized volatility of agricultural commodity prices: Does sentiment matter?," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 43(6), pages 2088-2125, September.
  17. Zhang, Yaojie & He, Mengxi & Wang, Yudong & Wen, Danyan, 2025. "Model specification for volatility forecasting benchmark," International Review of Financial Analysis, Elsevier, vol. 97(C).
  18. Li, Jianping & Li, Guowen & Liu, Mingxi & Zhu, Xiaoqian & Wei, Lu, 2022. "A novel text-based framework for forecasting agricultural futures using massive online news headlines," International Journal of Forecasting, Elsevier, vol. 38(1), pages 35-50.
  19. Salisu, Afees A. & Ogbonna, Ahamuefula E. & Gupta, Rangan & Bouri, Elie, 2025. "Forecasting spot and futures price volatility of agricultural commodities: The role of climate-related migration uncertainty," Research in International Business and Finance, Elsevier, vol. 80(C).
  20. Massimo Guidolin & Manuela Pedio, 2022. "Switching Coefficients or Automatic Variable Selection: An Application in Forecasting Commodity Returns," Forecasting, MDPI, vol. 4(1), pages 1-32, February.
  21. Bonato, Matteo & Cepni, Oguzhan & Gupta, Rangan & Pierdzioch, Christian, 2024. "Financial stress and realized volatility: The case of agricultural commodities," Research in International Business and Finance, Elsevier, vol. 71(C).
  22. Liu, Zhenhua & Wang, Yushu & Yuan, Xinting & Ding, Zhihua & Ji, Qiang, 2025. "Geopolitical risk and vulnerability of energy markets," Energy Economics, Elsevier, vol. 141(C).
  23. Ding, Yi & Kambouroudis, Dimos & McMillan, David G., 2025. "Forecasting realised volatility using regime-switching models," International Review of Economics & Finance, Elsevier, vol. 101(C).
  24. Algirdas Justinas Staugaitis & Bernardas Vaznonis, 2022. "Short-Term Speculation Effects on Agricultural Commodity Returns and Volatility in the European Market Prior to and during the Pandemic," Agriculture, MDPI, vol. 12(5), pages 1-26, April.
  25. Wuyue An & Lin Wang & Dongfeng Zhang, 2023. "Comprehensive commodity price forecasting framework using text mining methods," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(7), pages 1865-1888, November.
  26. Lang, Qiaoqi & Li, Chenyu & Wen, Lixuan & Wu, Hanlin, 2025. "Biodiversity risk and agricultural futures markets," International Review of Financial Analysis, Elsevier, vol. 107(C).
  27. Ava C. Blake & Nivika A. Gandhi & Anurag R. Jakkula, 2025. "Improving S&P 500 Volatility Forecasting through Regime-Switching Methods," Papers 2510.03236, arXiv.org.
  28. Chia‐Hsien Tang & Yen‐Hsien Lee & Hung‐Chun Liu & Guan‐Gzhe Zeng, 2024. "Exploring the unpredictable nature of climate policy uncertainty: An empirical analysis of its impact on commodity futures returns in the United States," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 44(7), pages 1277-1292, July.
  29. Sabri Boubaker & Zhenya Liu & Ling Zhai, 2025. "Change-points and functional features of intraday volatility in China stock market," Annals of Operations Research, Springer, vol. 352(3), pages 563-582, September.
  30. Luo, Jiawen & Marfatia, Hardik A. & Ji, Qiang & Klein, Tony, 2023. "Co-volatility and asymmetric transmission of risks between the global oil and China's futures markets," Energy Economics, Elsevier, vol. 117(C).
  31. Lu, Xinjie & Su, Yuandong & Huang, Dengshi, 2023. "Chinese agricultural futures volatility: New insights from potential domestic and global predictors," International Review of Financial Analysis, Elsevier, vol. 89(C).
  32. Dutta, Anupam & Uddin, Gazi Salah & Sheng, Lin Wen & Park, Donghyun & Zhu, Xuening, 2024. "Volatility dynamics of agricultural futures markets under uncertainties," Energy Economics, Elsevier, vol. 136(C).
  33. Lyócsa, Štefan & Todorova, Neda, 2024. "Forecasting of clean energy market volatility: The role of oil and the technology sector," Energy Economics, Elsevier, vol. 132(C).
  34. Matteo Bonato & Oğuzhan Çepni & Rangan Gupta & Christian Pierdzioch, 2023. "El Niño, La Niña, and forecastability of the realized variance of agricultural commodity prices: Evidence from a machine learning approach," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(4), pages 785-801, July.
  35. Najaf Iqbal & Elie Bouri & Oksana Grebinevych & David Roubaud, 2023. "Modelling extreme risk spillovers in the commodity markets around crisis periods including COVID19," Annals of Operations Research, Springer, vol. 330(1), pages 305-334, November.
IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.