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The influence of world oil prices on the Chinese Yuan exchange rate

Author

Listed:
  • Jaromír Vrbka

    (Institute of Technology and Business in České Budějovice, Czech Republic)

  • Jakub Horák

    (Institute of Technology and Business in České Budějovice, Czech Republic)

  • Tomáš Krulický

    (Institute of Technology and Business in České Budějovice, Czech Republic)

Abstract

This article aims to find out if and if any influence the evolution of oil price on the world market influences the value of the Chinese currency. Data, which we used for analysis, is available on the World Bank website. The analysis uses data about the Chinese Yuan (CNY) to the US Dollar (USD). The second series of data is the Brent crude oil price expressed in US Dollars per barrel. The time interval for which data will be available is the daily closing value of both variables, beginning on September 1, 2014, and ending on August 30, 2019. To accomplish our research aim, we must conduct an experiment. Therefore, the experiment assumes a uniform procedure with a gradual change of one parameter, namely the delay of the CNY / USD time series. Regression is performed using neural structures. We generate 10,000 neural networks for every single experiment combination (time delay, set of independent variables). As a result, we perform 10 calculations and get ten different outputs. From each experiment, we always preserve 5 artificial neural networks that show the best aspects. It could be estimated that fluctuations in oil prices on world markets would affect the CNY / USD price; however, it was not clear to what extent. Based on this paper, we demonstrate that such influence exists; it can be identified at an interval of 1.97% to 9.57%. This is a very significant influence, even regarding the importance of the raw material.

Suggested Citation

  • Jaromír Vrbka & Jakub Horák & Tomáš Krulický, 2022. "The influence of world oil prices on the Chinese Yuan exchange rate," Entrepreneurship and Sustainability Issues, VsI Entrepreneurship and Sustainability Center, vol. 9(4), pages 439-462, June.
    • Handle: RePEc:ssi:jouesi:v:9:y:2022:i:4:p:439-462
    DOI: 10.9770/jesi2022.9.4(24)
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    References listed on IDEAS

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    1. Amano, R. A. & van Norden, S., 1998. "Oil prices and the rise and fall of the US real exchange rate," Journal of International Money and Finance, Elsevier, vol. 17(2), pages 299-316, April.
    2. van Amano, Robert A & Norden, Simon, 1998. "Exchange Rates and Oil Prices," Review of International Economics, Wiley Blackwell, vol. 6(4), pages 683-694, November.
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    4. Robert B. Barsky & Lutz Kilian, 2004. "Oil and the Macroeconomy Since the 1970s," Journal of Economic Perspectives, American Economic Association, vol. 18(4), pages 115-134, Fall.
    5. Liu, Siyao & Fang, Wei & Gao, Xiangyun & An, Feng & Jiang, Meihui & Li, Yang, 2019. "Long-term memory dynamics of crude oil price spread in non-dollar countries under the influence of exchange rates," Energy, Elsevier, vol. 182(C), pages 753-764.
    6. Sam, B.A. TENDE & Ezie OBUMNEKE, 2014. "Impact of Petroleum on SMEs Growth in Nigeria," International Journal of Entrepreneurial Knowledge, Center for International Scientific Research of VSO and VSPP, vol. 2(2), pages 4-14, December.
    7. Baghestani, Hamid & Toledo, Hugo, 2019. "Oil prices and real exchange rates in the NAFTA region," The North American Journal of Economics and Finance, Elsevier, vol. 48(C), pages 253-264.
    8. Mirzosaid Sultonov, 2017. "The impacts of the oil price fall on the exchange rates of ASEAN-5: Evidence from the 2014 oil price shock," Economics Bulletin, AccessEcon, vol. 37(1), pages 468-479.
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    Cited by:

    1. Marek Vochozka & Svatopluk Janek & Zuzana Rowland, 2023. "Coffee as an Identifier of Inflation in Selected US Agglomerations," Forecasting, MDPI, vol. 5(1), pages 1-17, January.
    2. Jakub Horák & Michaela Jannová, 2023. "Predicting the Oil Price Movement in Commodity Markets in Global Economic Meltdowns," Forecasting, MDPI, vol. 5(2), pages 1-16, March.

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    More about this item

    Keywords

    world oil price; Chinese Yuan; exchange rate; artificial neural networks; price development; time series;
    All these keywords.

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C45 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Neural Networks and Related Topics
    • F31 - International Economics - - International Finance - - - Foreign Exchange

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