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The dependence structure analysis among gold price, stock price index of gold mining companies and Shanghai composite index

Author

Listed:
  • Xi Shen

    (Chiang Mai University)

  • Kanchana Chokethaworn

    (Chiang Mai University)

  • Chukiat Chaiboonsri

    (Chiang Mai University)

Abstract

This paper used different copula-based GARCH models (Copula-GARCH model and Copula-GJR-GARCH model) to analyze the dependence structure among gold price, stock price index of gold mining companies and Shanghai Composite Index in China. The empirical results found that the suitable margins were skew-t distribution, and the GJR-GARCH marginal distribution had better explanatory ability than the GARCH model. Moreover, we found the Clayton copula had the highest explanatory ability of the dependence structure for all series. There existed positive dependence in the rates of return for all series, and the dependence between these markets will be closer with the gradual integration of international financial market.

Suggested Citation

  • Xi Shen & Kanchana Chokethaworn & Chukiat Chaiboonsri, 2013. "The dependence structure analysis among gold price, stock price index of gold mining companies and Shanghai composite index," The Empirical Econometrics and Quantitative Economics Letters, Faculty of Economics, Chiang Mai University, vol. 2(4), pages 53-64, December.
    • Handle: RePEc:chi:journl:v:2:y:2013:i:4:p:53-64
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    References listed on IDEAS

    as
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    3. Blose, Laurence E. & Shieh, Joseph C. P., 1995. "The impact of gold price on the value of gold mining stock," Review of Financial Economics, Elsevier, vol. 4(2), pages 125-139.
    4. Glosten, Lawrence R & Jagannathan, Ravi & Runkle, David E, 1993. "On the Relation between the Expected Value and the Volatility of the Nominal Excess Return on Stocks," Journal of Finance, American Finance Association, vol. 48(5), pages 1779-1801, December.
    5. Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April.
    6. Garry Twite, 2002. "Gold Prices, Exchange Rates, Gold Stocks and the Gold Premium," Australian Journal of Management, Australian School of Business, vol. 27(2), pages 123-140, December.
    7. Andrew J. Patton, 2006. "Modelling Asymmetric Exchange Rate Dependence," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 47(2), pages 527-556, May.
    8. Hansen, Bruce E, 1994. "Autoregressive Conditional Density Estimation," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 35(3), pages 705-730, August.
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    Cited by:

    1. Lazzarino, Marco & Berrill, Jenny & Šević, Aleksandar, 2022. "The importance of distinguishing between precious and industrial metals when investing in mining stocks," Resources Policy, Elsevier, vol. 78(C).
    2. Talbi, Marwa & Bedoui, Rihab & de Peretti, Christian & Belkacem, Lotfi, 2021. "Is the role of precious metals as precious as they are? A vine copula and BiVaR approaches," Resources Policy, Elsevier, vol. 73(C).

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    More about this item

    Keywords

    Gold price; Shandong gold stock index; Shanghai composite index; Copula-GARCH; Skewed distribution;
    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
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)

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