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Contagion Between Gold and other Commodity Goods using Bayesian Multivariate Quantile_On_Quantile Approach

Author

Listed:
  • Hao Wen CHANG

    (Department of Finance, National Yang-Ming Chiao-Tung University, HsinChu, TAIWAN.)

  • Tsangyao CHANG

    (Department of Finance, Feng Chia University, Taichung, TAIWAN.)

  • Yang-Cheng LU

    (Department of Finance, Ming Chung University, Taipei, TAIWAN.)

Abstract

This study revisits Gold, Nickel, oil price, Copper, and Tin links using Bayesian Multivariate Quantile_on_Quantile approach over the period of 1960M1 to 2022M5. Where the GARCH (1,1) is considered when estimating the model to alleviate the heteroskedastic problem. Our findings show that the connections between Gold returns and other four commodity goods returns change across various quantiles. The GARCH model shows that previous information and persistence gauges vary with current conditional variance under different quantiles. Moreover, the half-life of a shock ranges from 0.38 to 3.72 months for all our markets, which was not found in the existing papers. Our findings provide prominent economic implications for investors, practitioners, and government.

Suggested Citation

  • Hao Wen CHANG & Tsangyao CHANG & Yang-Cheng LU, 2023. "Contagion Between Gold and other Commodity Goods using Bayesian Multivariate Quantile_On_Quantile Approach," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(2), pages 21-35, June.
    • Handle: RePEc:rjr:romjef:v::y:2023:i:2:p:21-35
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    References listed on IDEAS

    as
    1. Jain, Anshul & Biswal, P.C., 2016. "Dynamic linkages among oil price, gold price, exchange rate, and stock market in India," Resources Policy, Elsevier, vol. 49(C), pages 179-185.
    2. Behmiri, Niaz Bashiri & Manera, Matteo, 2015. "The role of outliers and oil price shocks on volatility of metal prices," Resources Policy, Elsevier, vol. 46(P2), pages 139-150.
    3. Antonakakis, Nikolaos & Breitenlechner, Max & Scharler, Johann, 2015. "Business cycle and financial cycle spillovers in the G7 countries," The Quarterly Review of Economics and Finance, Elsevier, vol. 58(C), pages 154-162.
    4. An, Sufang & Gao, Xiangyun & An, Haizhong & Liu, Siyao & Sun, Qingru & Jia, Nanfei, 2020. "Dynamic volatility spillovers among bulk mineral commodities: A network method," Resources Policy, Elsevier, vol. 66(C).
    5. Balcilar, Mehmet & Demirer, Rıza & Hammoudeh, Shawkat, 2019. "Quantile relationship between oil and stock returns: Evidence from emerging and frontier stock markets," Energy Policy, Elsevier, vol. 134(C).
    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    Bayesian; Quantile_on_Quantile; Gold; Commodity Goods; GARCH;
    All these keywords.

    JEL classification:

    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)

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