IDEAS home Printed from https://ideas.repec.org/r/eee/eneeco/v78y2019icp192-201.html
   My bibliography  Save this item

Do high-frequency stock market data help forecast crude oil prices? Evidence from the MIDAS models

Citations

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


Cited by:

  1. Hao-Lin Shao & Ying-Hui Shao & Yan-Hong Yang, 2021. "New insights into price drivers of crude oil futures markets: Evidence from quantile ARDL approach," Papers 2110.02693, arXiv.org.
  2. Wen, Jun & Zhao, Xin-Xin & Chang, Chun-Ping, 2021. "The impact of extreme events on energy price risk," Energy Economics, Elsevier, vol. 99(C).
  3. Xing, Li-Min & Zhang, Yue-Jun, 2022. "Forecasting crude oil prices with shrinkage methods: Can nonconvex penalty and Huber loss help?," Energy Economics, Elsevier, vol. 110(C).
  4. Bouri, Elie & Lei, Xiaojie & Jalkh, Naji & Xu, Yahua & Zhang, Hongwei, 2021. "Spillovers in higher moments and jumps across US stock and strategic commodity markets," Resources Policy, Elsevier, vol. 72(C).
  5. Wang, Fan & Tian, Lixin & Du, Ruijin & Dong, Gaogao, 2021. "Universal law in the crude oil market based on visibility graph algorithm and network structure," Resources Policy, Elsevier, vol. 70(C).
  6. Wen, Danyan & Liu, Li & Wang, Yudong & Zhang, Yaojie, 2022. "Forecasting crude oil market returns: Enhanced moving average technical indicators," Resources Policy, Elsevier, vol. 76(C).
  7. Qu, Fang & Chen, Yufeng & Zheng, Biao, 2021. "Is new energy driven by crude oil, high-tech sector or low-carbon notion? New evidence from high-frequency data," Energy, Elsevier, vol. 230(C).
  8. Lu-Tao Zhao & Li-Na Liu & Zi-Jie Wang & Ling-Yun He, 2019. "Forecasting Oil Price Volatility in the Era of Big Data: A Text Mining for VaR Approach," Sustainability, MDPI, vol. 11(14), pages 1-20, July.
  9. Paresh Kumar Narayan, 2021. "Oil Price News and COVID-19 - Is There Any Connection," Energy RESEARCH LETTERS, Asia-Pacific Applied Economics Association, vol. 1(1), pages 1-4.
  10. Zhang, Yue-Jun & Li, Zhao-Chen, 2021. "Forecasting the stock returns of Chinese oil companies: Can investor attention help?," International Review of Economics & Finance, Elsevier, vol. 76(C), pages 531-555.
  11. O-Chia Chuang & Chenxu Yang, 2022. "Identifying the Determinants of Crude Oil Market Volatility by the Multivariate GARCH-MIDAS Model," Energies, MDPI, vol. 15(8), pages 1-14, April.
  12. Mensi, Walid & Hammoudeh, Shawkat & Vinh Vo, Xuan & Hoon Kang, Sang, 2021. "Volatility spillovers between oil and equity markets and portfolio risk implications in the US and vulnerable EU countries," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 75(C).
  13. Zhang, Yaojie & He, Mengxi & Wen, Danyan & Wang, Yudong, 2023. "Forecasting crude oil price returns: Can nonlinearity help?," Energy, Elsevier, vol. 262(PB).
  14. Yue-Jun Zhang & Han Zhang & Rangan Gupta, 2021. "Forecasting the Artificial Intelligence Index Returns: A Hybrid Approach," Working Papers 202182, University of Pretoria, Department of Economics.
  15. Zhao, Geya & Xue, Minggao & Cheng, Li, 2023. "A new hybrid model for multi-step WTI futures price forecasting based on self-attention mechanism and spatial–temporal graph neural network," Resources Policy, Elsevier, vol. 85(PB).
  16. Xu Gong & Mingchao Wang & Liuguo Shao, 2022. "The impact of macro economy on the oil price volatility from the perspective of mixing frequency," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(4), pages 4487-4514, October.
  17. Walid Mensi & Mobeen Ur Rehman & Muhammad Shafiullah & Khamis Hamed Al-Yahyaee & Ahmet Sensoy, 2021. "High frequency multiscale relationships among major cryptocurrencies: portfolio management implications," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 7(1), pages 1-21, December.
  18. Yuandong, Su & Khaskheli, Asadullah & Raza, Syed Ali & Yousufi, Sara Qamar, 2022. "How COVID-19 influences prices of oil and precious metals: Comparison between data extracted from online searching trends and actual events," Resources Policy, Elsevier, vol. 78(C).
  19. Rice, Gregory & Wirjanto, Tony & Zhao, Yuqian, 2021. "Exploring volatility of crude oil intra-day return curves: a functional GARCH-X Model," MPRA Paper 109231, University Library of Munich, Germany.
  20. Zhang, Yuan-Yuan & Zhang, Yue-Jun, 2022. "The impact of institutional analyst forecast divergence on crude oil market: Evidence from the mixed frequency models," International Review of Financial Analysis, Elsevier, vol. 84(C).
  21. Arthur J. Lin & Hai-Yen Chang, 2020. "Volatility Transmission from Equity, Bulk Shipping, and Commodity Markets to Oil ETF and Energy Fund—A GARCH-MIDAS Model," Mathematics, MDPI, vol. 8(9), pages 1-21, September.
  22. Yang, Jianlei & Yang, Chunpeng, 2021. "The impact of mixed-frequency geopolitical risk on stock market returns," Economic Analysis and Policy, Elsevier, vol. 72(C), pages 226-240.
  23. Hao, Yu & Gai, Zhiqiang & Wu, Haitao, 2020. "How do resource misallocation and government corruption affect green total factor energy efficiency? Evidence from China," Energy Policy, Elsevier, vol. 143(C).
  24. Zhang, Yue-Jun & Yan, Xing-Xing, 2020. "The impact of US economic policy uncertainty on WTI crude oil returns in different time and frequency domains," International Review of Economics & Finance, Elsevier, vol. 69(C), pages 750-768.
  25. Zhang, Yue-Jun & Ma, Shu-Jiao, 2019. "How to effectively estimate the time-varying risk spillover between crude oil and stock markets? Evidence from the expectile perspective," Energy Economics, Elsevier, vol. 84(C).
  26. Yufeng Lin & Xiaogang Wang & Yuehua Wu, 2023. "An Adaptive Multiple-Asset Portfolio Strategy with User-Specified Risk Tolerance," Mathematics, MDPI, vol. 11(7), pages 1-35, March.
  27. Ghaemi Asl, Mahdi & Adekoya, Oluwasegun Babatunde & Rashidi, Muhammad Mahdi & Ghasemi Doudkanlou, Mohammad & Dolatabadi, Ali, 2022. "Forecast of Bayesian-based dynamic connectedness between oil market and Islamic stock indices of Islamic oil-exporting countries: Application of the cascade-forward backpropagation network," Resources Policy, Elsevier, vol. 77(C).
  28. 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).
  29. Razmi, Seyedeh Fatemeh & Razmi, Seyed Mohammad Javad, 2023. "The role of stock markets in the US, Europe, and China on oil prices before and after the COVID-19 announcement," Resources Policy, Elsevier, vol. 81(C).
  30. Leng, Na & Li, Jiang-Cheng, 2020. "Forecasting the crude oil prices based on Econophysics and Bayesian approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 554(C).
  31. Daniel Ştefan Armeanu & Camelia Cătălina Joldeş & Ştefan Cristian Gherghina, 2019. "On the Linkage between the Energy Market and Stock Returns: Evidence from Romania," Energies, MDPI, vol. 12(8), pages 1-21, April.
  32. Ouyang, Zi-sheng & Liu, Meng-tian & Huang, Su-su & Yao, Ting, 2022. "Does the source of oil price shocks matter for the systemic risk?," Energy Economics, Elsevier, vol. 109(C).
  33. He, Huizi & Sun, Mei & Gao, Cuixia & Li, Xiuming, 2021. "Detecting lag linkage effect between economic policy uncertainty and crude oil price: A multi-scale perspective," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 580(C).
  34. Guo, Yaoqi & Shi, Fengyuan & Lin, Boqiang & Zhang, Hongwei, 2023. "The impact of oil shocks from different sources on China's clean energy metal stocks: An analysis of spillover effects based on a time-varying perspective," Resources Policy, Elsevier, vol. 81(C).
  35. Qing Peng & Fenghua Wen & Xu Gong, 2021. "Time‐dependent intrinsic correlation analysis of crude oil and the US dollar based on CEEMDAN," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(1), pages 834-848, January.
  36. Ding, Lili & Zhao, Zhongchao & Wang, Lei, 2022. "Probability density forecasts for natural gas demand in China: Do mixed-frequency dynamic factors matter?," Applied Energy, Elsevier, vol. 312(C).
  37. Yue-Jun Zhang & Han Zhang & Rangan Gupta, 2023. "A new hybrid method with data-characteristic-driven analysis for artificial intelligence and robotics index return forecasting," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 9(1), pages 1-23, December.
  38. Zhang, Yue-Jun & Lin, Jia-Juan, 2019. "Can the VAR model outperform MRS model for asset allocation in commodity market under different risk preferences of investors?," International Review of Financial Analysis, Elsevier, vol. 66(C).
  39. Alper Gormus & Ugur Soytas, 2023. "Financial Sector Troubles and Energy Markets," International Journal of Energy Economics and Policy, Econjournals, vol. 13(2), pages 357-363, March.
  40. 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.
  41. Bhatia, Vaneet & Basu, Sankarshan, 2021. "Causality-in-quantiles between crude oil and stock markets: Evidence from emerging economies," Finance Research Letters, Elsevier, vol. 40(C).
  42. Kliber, Agata & Łęt, Blanka, 2022. "Degree of connectedness and the transfer of news across the oil market and the European stocks," Energy, Elsevier, vol. 239(PC).
  43. Yingchao Zou & Kaijian He, 2022. "Forecasting Crude Oil Risk Using a Multivariate Multiscale Convolutional Neural Network Model," Mathematics, MDPI, vol. 10(14), pages 1-11, July.
  44. Yue-Jun Zhang & Shu-Hui Li, 2019. "The impact of investor sentiment on crude oil market risks: evidence from the wavelet approach," Quantitative Finance, Taylor & Francis Journals, vol. 19(8), pages 1357-1371, August.
  45. Ding, Lili & Zhao, Zhongchao & Han, Meng, 2021. "Probability density forecasts for steam coal prices in China: The role of high-frequency factors," Energy, Elsevier, vol. 220(C).
  46. Arthur Jin Lin, 2023. "Volatility Contagion from Bulk Shipping and Petrochemical Industries to Oil Futures Market during the Economic Uncertainty," Mathematics, MDPI, vol. 11(17), pages 1-19, August.
IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.