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Dynamic Price Integration in the Global Gold Market

Author

Listed:
  • Chang, Chia-Lin
  • Chang, Jui-Chuan Della
  • Huang, Yi-Wei

Abstract

This paper examines the inter-relationships among gold prices in five global gold markets, namely London, New York, Japan, Hong Kong (since 1 July 1997, a Special Administrative Region (SAR) of China), and Taiwan. We investigate the linkages between Taiwan and the other global gold markets to provide insights for useful investment strategies. The augmenting level-VAR models proposed by Toda and Yamamoto (1995) show that the empirical results find bi-directional causality between the London and New York gold markets, and uni-directional causality from New York to the other markets. In this sense, the New York market has gained a leading role in affecting global gold markets. This empirical finding serves as a predictor for the gold price in global markets.

Suggested Citation

  • Chang, Chia-Lin & Chang, Jui-Chuan Della & Huang, Yi-Wei, 2012. "Dynamic Price Integration in the Global Gold Market," MPRA Paper 41627, University Library of Munich, Germany.
  • Handle: RePEc:pra:mprapa:41627
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    References listed on IDEAS

    as
    1. Hammoudeh, Shawkat & Malik, Farooq & McAleer, Michael, 2011. "Risk management of precious metals," The Quarterly Review of Economics and Finance, Elsevier, vol. 51(4), pages 435-441.
    2. Engle, Robert & Granger, Clive, 2015. "Co-integration and error correction: Representation, estimation, and testing," Applied Econometrics, Publishing House "SINERGIA PRESS", vol. 39(3), pages 106-135.
    3. Hammoudeh, Shawkat M. & Yuan, Yuan & McAleer, Michael & Thompson, Mark A., 2010. "Precious metals-exchange rate volatility transmissions and hedging strategies," International Review of Economics & Finance, Elsevier, vol. 19(4), pages 633-647, October.
    4. Beckmann, Joscha & Czudaj, Robert, 2013. "Gold as an inflation hedge in a time-varying coefficient framework," The North American Journal of Economics and Finance, Elsevier, vol. 24(C), pages 208-222.
    5. Johansen, Soren & Juselius, Katarina, 1990. "Maximum Likelihood Estimation and Inference on Cointegration--With Applications to the Demand for Money," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 52(2), pages 169-210, May.
    6. Zapata, Hector O & Rambaldi, Alicia N, 1997. "Monte Carlo Evidence on Cointegration and Causation," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 59(2), pages 285-298, May.
    7. Capie, Forrest & Mills, Terence C. & Wood, Geoffrey, 2005. "Gold as a hedge against the dollar," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 15(4), pages 343-352, October.
    8. M. Hashem Pesaran & Yongcheol Shin & Richard J. Smith, 2001. "Bounds testing approaches to the analysis of level relationships," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 16(3), pages 289-326.
    9. Granger, C W J, 1969. "Investigating Causal Relations by Econometric Models and Cross-Spectral Methods," Econometrica, Econometric Society, vol. 37(3), pages 424-438, July.
    10. Nicholas Taylor, 1998. "Precious metals and inflation," Applied Financial Economics, Taylor & Francis Journals, vol. 8(2), pages 201-210.
    11. Granger, C. W. J., 1988. "Some recent development in a concept of causality," Journal of Econometrics, Elsevier, vol. 39(1-2), pages 199-211.
    12. MacKinnon, James G, 1996. "Numerical Distribution Functions for Unit Root and Cointegration Tests," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 11(6), pages 601-618, Nov.-Dec..
    13. Toda, Hiro Y. & Yamamoto, Taku, 1995. "Statistical inference in vector autoregressions with possibly integrated processes," Journal of Econometrics, Elsevier, vol. 66(1-2), pages 225-250.
    14. Sims, Christopher A & Stock, James H & Watson, Mark W, 1990. "Inference in Linear Time Series Models with Some Unit Roots," Econometrica, Econometric Society, vol. 58(1), pages 113-144, January.
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    Citations

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    Cited by:

    1. Chia-Lin Chang & Allen, David & McAleer, Michael, 2013. "Recent developments in financial economics and econometrics: An overview," The North American Journal of Economics and Finance, Elsevier, vol. 26(C), pages 217-226.
    2. Antunes, João Marques & Fuinhas, José Alberto & Marques, António Cardoso, 2014. "Modelização VAR da volatilidade dos preços do ouro e dos índices dos mercados financeiros
      [Modelling the volatility of gold prices and financial stock indexes: a VAR approach]
      ," MPRA Paper 57017, University Library of Munich, Germany.
    3. repec:eee:phsmap:v:490:y:2018:i:c:p:504-512 is not listed on IDEAS
    4. Ntim, Collins G. & English, John & Nwachukwu, Jacinta & Wang, Yan, 2015. "On the efficiency of the global gold markets," International Review of Financial Analysis, Elsevier, vol. 41(C), pages 218-236.
    5. repec:rss:jnljee:v3i1p3 is not listed on IDEAS
    6. repec:eee:jrpoli:v:52:y:2017:i:c:p:358-365 is not listed on IDEAS
    7. Wang, Gang-Jin & Xie, Chi & Jiang, Zhi-Qiang & Stanley, H. Eugene, 2016. "Extreme risk spillover effects in world gold markets and the global financial crisis," International Review of Economics & Finance, Elsevier, vol. 46(C), pages 55-77.

    More about this item

    Keywords

    Global gold market; Dynamic price integration; Toda-Yamamoto Procedure; Augmenting level-VAR models;

    JEL classification:

    • E31 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Price Level; Inflation; Deflation
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes

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