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The Asymmetric Long-Run Relationship Between Crude Oil And Gold Futures

Author

Listed:
  • Yen-Hsien Lee
  • Ya-Ling Huang
  • Hao-Jang Yang

Abstract

This study employs the momentum threshold error-correction model with generalized autoregressive conditional heteroskedasticity to investigate asymmetric cointegration and causal relationships between West Texas Intermediate Crude Oil and gold prices in the futures market. The paper examines data from May 1, 1994 to November 20, 2008. The empirical results show that an asymmetric long-run adjustment exists between gold and oil. Furthermore, the causality relationship shows that West Texas Intermediate Crude Oil plays a dominant role. The findings should prove valuable to individual investors and financial institutions who can use the findings here to gold prices based on oil prices.

Suggested Citation

  • Yen-Hsien Lee & Ya-Ling Huang & Hao-Jang Yang, 2012. "The Asymmetric Long-Run Relationship Between Crude Oil And Gold Futures," Global Journal of Business Research, The Institute for Business and Finance Research, vol. 6(1), pages 9-15.
    • Handle: RePEc:ibf:gjbres:v:6:y:2012:i:1:p:9-15
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    References listed on IDEAS

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    3. Mehmet Balcilar & Zeynel Abidin Ozdemir & Muhammad Shahbaz, 2019. "On the time‐varying links between oil and gold: New insights from the rolling and recursive rolling approaches," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 24(3), pages 1047-1065, July.
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    5. Gülfen TUNA, 2017. "Time Varying Causality Between Gold And Oil Prices," Romanian Economic Business Review, Romanian-American University, vol. 12(1), pages 59-67, March.
    6. Mokni, Khaled & Hammoudeh, Shawkat & Ajmi, Ahdi Noomen & Youssef, Manel, 2020. "Does economic policy uncertainty drive the dynamic connectedness between oil price shocks and gold price?," Resources Policy, Elsevier, vol. 69(C).
    7. Chkili, Walid, 2015. "Gold-oil prices co-movements and portfolio diversification implications," MPRA Paper 68110, University Library of Munich, Germany.
    8. Luqman, Muhammad & Mugheri, Adil & Ahmad, Najid & Soytas, Ugur, 2023. "Casting shadows on natural resource commodity markets: Unraveling the quantile dilemma of gold and crude oil prices," Resources Policy, Elsevier, vol. 86(PA).
    9. Kanjilal, Kakali & Ghosh, Sajal, 2017. "Dynamics of crude oil and gold price post 2008 global financial crisis – New evidence from threshold vector error-correction model," Resources Policy, Elsevier, vol. 52(C), pages 358-365.
    10. Gil-Alana, Luis A. & Yaya, OlaOluwa S. & Awe, Olushina O., 2017. "Time series analysis of co-movements in the prices of gold and oil: Fractional cointegration approach," Resources Policy, Elsevier, vol. 53(C), pages 117-124.
    11. Shahbaz, Muhammad & Balcilar, Mehmet & Abidin Ozdemir, Zeynel, 2017. "Does oil predict gold? A nonparametric causality-in-quantiles approach," Resources Policy, Elsevier, vol. 52(C), pages 257-265.
    12. Zhang, Chuanguo & Liu, Feng & Yu, Danlin, 2018. "Dynamic jumps in global oil price and its impacts on China's bulk commodities," Energy Economics, Elsevier, vol. 70(C), pages 297-306.
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    16. İrfan Civcir & Uğur Akkoç, 2021. "Dynamic volatility linkages and hedging between commodities and sectoral stock returns in Turkey: Evidence from SVAR‐cDCC‐GARCH model," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(2), pages 1978-1992, April.
    17. Akkoc, Ugur & Civcir, Irfan, 2019. "Dynamic linkages between strategic commodities and stock market in Turkey: Evidence from SVAR-DCC-GARCH model," Resources Policy, Elsevier, vol. 62(C), pages 231-239.
    18. Tiwari, Aviral Kumar & Sahadudheen, I., 2015. "Understanding the nexus between oil and gold," Resources Policy, Elsevier, vol. 46(P2), pages 85-91.

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    More about this item

    Keywords

    Momentum Threshold Error Correction Model; Asymmetric Causality Relationship; Crude Oil; Gold; Futures Market;
    All these keywords.

    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets
    • Q39 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Nonrenewable Resources and Conservation - - - Other
    • Q49 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Other

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