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On the Predictability and Resilience of Gold Prices’ Returns and Volatility

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  • John Francis T. Diaz

Abstract

Utilizing forty-five years of daily London gold price fixes, this paper finds the presence of dual long-memory processes in the 10:30am fix and the 3:00pm price fix utilizing ARFIMA-FIGARCH and ARFIMA-FIEGARCH models, respectively. This research proves that the return and volatility of the London Gold price fixes have predictable structures and does not conform to the weakform efficient assumption of Fama (1970). This study also suggests that the London gold price fixes do not exhibit leverage effects and asymmetric volatility response properties. This means that gold as an investment is generally immune to negative shocks, proving the resilience of gold as financial instrument. This paper also reveals the ARFIMA-FIAPARCH models have better fit in modeling the morning gold fix, while the ARFIMA-FIEGARCH model is more suitable in modeling the afternoon gold fix.

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  • John Francis T. Diaz, 2016. "On the Predictability and Resilience of Gold Prices’ Returns and Volatility," Journal of Applied Finance & Banking, SCIENPRESS Ltd, vol. 6(6), pages 1-2.
    • Handle: RePEc:spt:apfiba:v:6:y:2016:i:6:f:6_6_2
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    References listed on IDEAS

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    1. Baur, Dirk G. & McDermott, Thomas K., 2010. "Is gold a safe haven? International evidence," Journal of Banking & Finance, Elsevier, vol. 34(8), pages 1886-1898, August.
    2. Dirk G. Baur & Brian M. Lucey, 2010. "Is Gold a Hedge or a Safe Haven? An Analysis of Stocks, Bonds and Gold," The Financial Review, Eastern Finance Association, vol. 45(2), pages 217-229, May.
    3. Harry Markowitz, 1952. "Portfolio Selection," Journal of Finance, American Finance Association, vol. 7(1), pages 77-91, March.
    4. Baillie, Richard T. & Bollerslev, Tim & Mikkelsen, Hans Ole, 1996. "Fractionally integrated generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 74(1), pages 3-30, September.
    5. Baillie, Richard T., 1996. "Long memory processes and fractional integration in econometrics," Journal of Econometrics, Elsevier, vol. 73(1), pages 5-59, July.
    6. Fama, Eugene F, 1970. "Efficient Capital Markets: A Review of Theory and Empirical Work," Journal of Finance, American Finance Association, vol. 25(2), pages 383-417, May.
    7. Cheung, Yin-Wong & Lai, Kon S, 1993. "Do Gold Market Returns Have Long Memory?," The Financial Review, Eastern Finance Association, vol. 28(2), pages 181-202, May.
    8. Seung‐Ryong Yang & B. Wade Brorsen, 1993. "Nonlinear dynamics of daily futures prices: Conditional heteroskedasticity or chaos?," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 13(2), pages 175-191, April.
    9. Murray Frank & Thanasis Stengos, 1989. "Measuring the Strangeness of Gold and Silver Rates of Return," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 56(4), pages 553-567.
    10. C. W. J. Granger & Roselyne Joyeux, 1980. "An Introduction To Long‐Memory Time Series Models And Fractional Differencing," Journal of Time Series Analysis, Wiley Blackwell, vol. 1(1), pages 15-29, January.
    11. Y. K. Tse, 1998. "The conditional heteroscedasticity of the yen-dollar exchange rate," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 13(1), pages 49-55.
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