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The influence of international oil prices on the exchange rates of oil exporting countries: Based on the hybrid copula function

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  • Wang, Jianzhou
  • Niu, Xinsong
  • Zhang, Lifang
  • Liu, Zhenkun
  • Wei, Danxiang

Abstract

Achieving accurate exchange rate forecasts has a significant impact in construction of international trade and currency markets. However, because of the volatility of exchange rate series, accurate exchange rate prediction is still a difficult issue. In prior studies, researchers tend to conduct prediction research on individual variables of the real exchange rate and ignore the direct influence of other relevant economic factors on the real exchange rate forecasts, which leads to unsatisfactory prediction accuracy. At present, oil price shocks are often used as the dominant factor to explain the actual exchange rate behavior, and the analysis of the relationship between the two has become a hot issue. To explore the direct impact of oil prices on the real effective exchange rate forecast, a bivariate scheme is proposed, proving the important effect of oil price variable on exchange rate forecasting. The framework of this article starts from two aspects. First, several Copula functions are used to study the relationship between the two sequences, and the basic Copula functions including Clayton, Gumbel, and Frank functions are selected, and the three Copula functions are employed to obtain a hybrid Copula function using the improved Dragonfly optimization strategy. Next, a binary forecasting framework is constructed and a data preprocessing method is added to construct a forecasting model. Finally, this article demonstrates that the bivariate scheme achieves better forecasting capabilities than the univariate forecasting frame.

Suggested Citation

  • Wang, Jianzhou & Niu, Xinsong & Zhang, Lifang & Liu, Zhenkun & Wei, Danxiang, 2022. "The influence of international oil prices on the exchange rates of oil exporting countries: Based on the hybrid copula function," Resources Policy, Elsevier, vol. 77(C).
    • Handle: RePEc:eee:jrpoli:v:77:y:2022:i:c:s0301420722001829
    DOI: 10.1016/j.resourpol.2022.102734
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    Cited by:

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    2. Huang, Menghao & Shao, Wei & Wang, Jian, 2023. "Correlations between the crude oil market and capital markets under the Russia–Ukraine conflict: A perspective of crude oil importing and exporting countries," Resources Policy, Elsevier, vol. 80(C).
    3. Zhang, Dongxue & Wang, Shuai & Liang, Yuqiu & Du, Zhiyuan, 2023. "A novel combined model for probabilistic load forecasting based on deep learning and improved optimizer," Energy, Elsevier, vol. 264(C).
    4. Niu, Xinsong & Wang, Jiyang & Wei, Danxiang & Zhang, Lifang, 2022. "A combined forecasting framework including point prediction and interval prediction for carbon emission trading prices," Renewable Energy, Elsevier, vol. 201(P1), pages 46-59.
    5. Sokhanvar, Amin & Çiftçioğlu, Serhan & Lee, Chien-Chiang, 2023. "The effect of energy price shocks on commodity currencies during the war in Ukraine," Resources Policy, Elsevier, vol. 82(C).
    6. Nakorji Musa & Oji-okoro Izuchukwu & Seyi Saint Akadiri, 2024. "Assessment of exchange rate determination in a mono-resource economy: A case of Nigeria," Journal of Economic Analysis, Anser Press, vol. 3(2), pages 101-120, June.
    7. Guo, Honggang & Wang, Jianzhou & Li, Zhiwu & Lu, Haiyan & Zhang, Linyue, 2022. "A non-ferrous metal price ensemble prediction system based on innovative combined kernel extreme learning machine and chaos theory," Resources Policy, Elsevier, vol. 79(C).
    8. Yang, Hufang & Jiang, Ping & Wang, Ying & Li, Hongmin, 2022. "A fuzzy intelligent forecasting system based on combined fuzzification strategy and improved optimization algorithm for renewable energy power generation," Applied Energy, Elsevier, vol. 325(C).
    9. Wang, Jianzhou & Gao, Jialu & Wei, Danxiang, 2022. "Electric load prediction based on a novel combined interval forecasting system," Applied Energy, Elsevier, vol. 322(C).
    10. Wang, Jianzhou & Xing, Qianyi & Zeng, Bo & Zhao, Weigang, 2022. "An ensemble forecasting system for short-term power load based on multi-objective optimizer and fuzzy granulation," Applied Energy, Elsevier, vol. 327(C).
    11. Amin Sokhanvar & Chien-Chiang Lee, 2023. "How do energy price hikes affect exchange rates during the war in Ukraine?," Empirical Economics, Springer, vol. 64(5), pages 2151-2164, May.

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