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Hasraddin Guliyev

Personal Details

First Name:Hasraddin
Middle Name:
Last Name:Guliyev
Suffix:
RePEc Short-ID:pgu860
[This author has chosen not to make the email address public]

Affiliation

Azərbaycan Dövlət İqtisad Universiteti

Baku, Azerbaijan
http://www.unec.edu.az/
RePEc:edi:aseuuaz (more details at EDIRC)

Research output

as
Jump to: Articles Software

Articles

  1. Guliyev, Hasraddin & Mustafayev, Eldayag, 2022. "Predicting the changes in the WTI crude oil price dynamics using machine learning models," Resources Policy, Elsevier, vol. 77(C).
  2. Famil Majidli & Hasraddin Guliyev, 2020. "How Oil Price and Exchange Rate Affect Non-oil GDP of the Oil-rich Country Azerbaijan?," International Journal of Energy Economics and Policy, Econjournals, vol. 10(5), pages 123-130.

Software components

  1. Hasraddin Guliyev, 2025. "BIASTEST: Stata module to test parameter equality across different models," Statistical Software Components S459437, Boston College Department of Economics, revised 08 May 2025.
  2. Hasraddin Guliyev, 2025. "XTSURMG: Stata module implementing Fourier Seemingly Unrelated Regression Mean Group Estimator," Statistical Software Components S459447, Boston College Department of Economics.

Citations

Many of the citations below have been collected in an experimental project, CitEc, where a more detailed citation analysis can be found. These are citations from works listed in RePEc that could be analyzed mechanically. So far, only a minority of all works could be analyzed. See under "Corrections" how you can help improve the citation analysis.

Articles

  1. Guliyev, Hasraddin & Mustafayev, Eldayag, 2022. "Predicting the changes in the WTI crude oil price dynamics using machine learning models," Resources Policy, Elsevier, vol. 77(C).

    Cited by:

    1. Jean-Michel Sahut & Petr Hajek & Vladimir Olej & Lubica Hikkerova, 2025. "The role of news-based sentiment in forecasting crude oil price during the Covid-19 pandemic," Annals of Operations Research, Springer, vol. 345(2), pages 861-884, February.
    2. Chuandi Fang & Jinhua Cheng & Zhe You & Jiahao Chen & Jing Peng, 2023. "A Detailed Examination of China’s Clean Energy Mineral Consumption: Footprints, Trends, and Drivers," Sustainability, MDPI, vol. 15(23), pages 1-26, November.
    3. Yu, Yue & Wang, Jianzhou & Jiang, He & Lu, Haiyan, 2025. "How to manage a multifactor-driven crude oil market more effectively? A revisit based on the multiple criteria perspective," Resources Policy, Elsevier, vol. 100(C).
    4. Yuyang, Liu, 2024. "Natural resource efficiency and the road to a green economy: From scarcity to availability," Resources Policy, Elsevier, vol. 89(C).
    5. Gkillas, Konstantinos & Manickavasagam, Jeevananthan & Visalakshmi, S., 2022. "Effects of fundamentals, geopolitical risk and expectations factors on crude oil prices," Resources Policy, Elsevier, vol. 78(C).
    6. Vicknair, David & Tansey, Michael & O'Brien, Thomas E., 2022. "Measuring fossil fuel reserves: A simulation and review of the U.S. Securities and Exchange Commission approach," Resources Policy, Elsevier, vol. 79(C).
    7. Zhang, Zhenya & Chang, Zheren & Gan, Yufei & Li, Jiayan, 2025. "Renewable energy, innovation, and stock markets: Machine learning perspectives on environmental sustainability," International Review of Financial Analysis, Elsevier, vol. 97(C).
    8. Jiang, Lan & Jiang, Hua, 2023. "Analysis of predictions considering mineral prices, residential energy, and environmental risk: Evidence from the USA in COP 26 perspective," Resources Policy, Elsevier, vol. 82(C).
    9. Xu, Kunliang & Wang, Weiqing, 2023. "Limited information limits accuracy: Whether ensemble empirical mode decomposition improves crude oil spot price prediction?," International Review of Financial Analysis, Elsevier, vol. 87(C).
    10. Ma, Yilin & Wang, Yudong & Wang, Weizhong & Zhang, Chong, 2023. "Portfolios with return and volatility prediction for the energy stock market," Energy, Elsevier, vol. 270(C).
    11. Emanuel Kohlscheen, 2024. "Forecasting oil prices with random forests," Empirical Economics, Springer, vol. 66(2), pages 927-943, February.
    12. Zhang, Xiheng & Liu, Jiayu & Zhang, Kaiqi & Robert, James, 2023. "Analysis of firm performance in presence of oil price shocks: Importance of skilled management," Resources Policy, Elsevier, vol. 86(PA).
    13. Zhang, Jiahao & Chen, Xiaodan & Wei, Yu & Bai, Lan, 2023. "Does the connectedness among fossil energy returns matter for renewable energy stock returns? Fresh insights from the Cross-Quantilogram analysis," International Review of Financial Analysis, Elsevier, vol. 88(C).
    14. Ding, Lili & Zhao, Haoran & Zhang, Rui, 2024. "Predicting multi-frequency crude oil price dynamics: Based on MIDAS and STL methods," Energy, Elsevier, vol. 313(C).
    15. Xu, Bin & Lin, Boqiang, 2023. "Assessing the green energy development in China and its carbon reduction effect: Using a quantile approach," Energy Economics, Elsevier, vol. 126(C).
    16. Chen, Fu & Tiwari, Sunil & Mohammed, Kamel Si & Huo, Weidong & Jamróz, Paweł, 2023. "Minerals resource rent responses to economic performance, greener energy, and environmental policy in China: Combination of ML and ANN outputs," Resources Policy, Elsevier, vol. 81(C).
    17. Taskin, Dilvin & Sariyer, Görkem & Acar, Ece & Cagli, Efe Caglar, 2025. "Do past ESG scores efficiently predict future ESG performance?," Research in International Business and Finance, Elsevier, vol. 74(C).
    18. Shucheng Lin & Yue Wang & Haocheng Wei & Xiaoyi Wang & Zhong Wang, 2025. "Hybrid Method for Oil Price Prediction Based on Feature Selection and XGBOOST-LSTM," Energies, MDPI, vol. 18(9), pages 1-27, April.
    19. Hyeon-Seok Kim & Hui-Sang Kim & Sun-Yong Choi, 2024. "Investigating the Impact of Agricultural, Financial, Economic, and Political Factors on Oil Forward Prices and Volatility: A SHAP Analysis," Energies, MDPI, vol. 17(5), pages 1-24, February.
    20. Liang, Xuedong & Luo, Peng & Li, Xiaoyan & Wang, Xia & Shu, Lingli, 2023. "Crude oil price prediction using deep reinforcement learning," Resources Policy, Elsevier, vol. 81(C).
    21. Liu, Jiexian, 2024. "Analyzing the Co-movement of FinTech market efficiency and oil Resource efficiency: An Input-Output study," Resources Policy, Elsevier, vol. 90(C).
    22. Sen, Doruk & Hamurcuoglu, K. Irem & Ersoy, Melisa Z. & Tunç, K.M. Murat & Günay, M. Erdem, 2023. "Forecasting long-term world annual natural gas production by machine learning," Resources Policy, Elsevier, vol. 80(C).
    23. Qiang Cao & Qin Hong & Wenmei Yu, 2025. "Oil price shocks, policy uncertainty, and China’s carbon emissions trading market price," Palgrave Communications, Palgrave Macmillan, vol. 12(1), pages 1-11, December.

  2. Famil Majidli & Hasraddin Guliyev, 2020. "How Oil Price and Exchange Rate Affect Non-oil GDP of the Oil-rich Country Azerbaijan?," International Journal of Energy Economics and Policy, Econjournals, vol. 10(5), pages 123-130.

    Cited by:

    1. Nigar Huseynli, 2022. "Impact of Revenues from Oil and Non-Oil Sectors on the Economic Growth of Azerbaijan," International Journal of Energy Economics and Policy, Econjournals, vol. 12(5), pages 31-35, September.
    2. Faiez Ahmed Elneel & Abdullah Fahad AlMulhim‎, 2022. "The Effect of Oil Price Shocks on Saudi Arabia’s Economic Growth in the Light of Vision 2030 “A Combination of VECM and ARDL Models”," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), vol. 13(4), pages 3401-3423, December.
    3. Nurkhodzha Akbulaev & Elshan Mammadli & Gadir Bayramli, 2022. "The Effect of Energy Prices on Stock Indices in the Period of COVID-19: Evidence from Russia, Turkey, Brazil, and India," International Journal of Energy Economics and Policy, Econjournals, vol. 12(3), pages 262-269, May.
    4. Shafa Guliyeva, 2023. "Analysis of the effect of Energy Prices on Stock Indexes During the Epidemic Crisis," International Journal of Energy Economics and Policy, Econjournals, vol. 13(2), pages 526-536, March.
    5. Ivan Aleksandrovich Kopytin & Nikolay Petrovich Pilnik & Ivan Pavlovich Stankevich, 2021. "Modelling Five Variables BVAR for Economic Policies and Growth in Azerbaijan, Kazakhstan and Russia: 2005 2020," International Journal of Energy Economics and Policy, Econjournals, vol. 11(5), pages 510-518.
    6. Rabiu Maijama’a & Kabiru Saidu Musa, 2021. "Crude Oil Price, Interest Rate and Unemployment Nexus in Nigeria: An Application of Toda and Yamamoto Long-Run Causality Procedure," Marketing and Branding Research, EUROKD, vol. 8(1), pages 1-16.

Software components

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