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The Seasonal Effect on the Chinese Gold Market using an Empirical Analysis of the Shanghai Gold Exchange

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  • Bing Xiao

    (University of Clermont Auvergne, France)

  • Philippe Maillebuau

    (University of Clermont Auvergne, France)

Abstract

Gold is considered as a hedge against inflation, it offers an opportunity for portfolio diversification. This paper examines the recent evolution of seasonal anomalies in the Chinese Gold market. It studies the day of the week effect and the monthly effect through gold prices at the Shanghai Gold Exchange (SGE) over the 2002 to 2016 period. We investigate seasonal patterns in economically favorable times and unfavorable times by using a UCM model and an ARCH model. The reforms in regulations have rendered the Chinese financial market more efficient, in such cases; we expect an alteration in seasonal anomalies in the Chinese Gold market. However, it would seem that seasonality does exist in the Chinese Gold Market. The Monday returns have been positive and the Tuesday returns have been negative for the whole period. We also highlight that January and February generate the best returns. The return in the middle of the year is negative. This paper contributes to the existing finance literature by investigating the anomalies during the recent period. Although in the Chinese stock market, the seasonal anomalies persist, the index may be efficient despite the regularity in price formation, in this case, a study over a more recent period is necessary.

Suggested Citation

  • Bing Xiao & Philippe Maillebuau, 2020. "The Seasonal Effect on the Chinese Gold Market using an Empirical Analysis of the Shanghai Gold Exchange," Eurasian Journal of Economics and Finance, Eurasian Publications, vol. 8(2), pages 104-114.
    • Handle: RePEc:ejn:ejefjr:v:8:y:2020:i:2:p:104-114
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    References listed on IDEAS

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    Cited by:

    1. Rupel Nargunam & William W. S. Wei & N. Anuradha, 2021. "Investigating seasonality, policy intervention and forecasting in the Indian gold futures market: a comparison based on modeling non-constant variance using two different methods," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 7(1), pages 1-15, December.

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