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Can futures price be a powerful predictor? Frequency domain analysis on Chinese commodity market

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  • Yang, Linghubo
  • Zhang, Dongxiang

Abstract

This paper presents the causal relationships between futures and spot prices of six metal and agriculture commodities in Chinese commodity market, using GC test, frequency domain approach proposed by Brietung and Candelon (2006) and Garbade–Silber (G–S) Model. Frequency domain approach indicates that futures price of each commodity is really a powerful predictor for spot price in both long and short terms, but not vice versa. From the results of G–S model, futures price of each commodity decides more than 70% of the price movements, which plays a dominant role in price discovering process. There are bi-directional casual relationships between futures and spot prices of all the six commodities excluding aluminum (Al) from the conclusions of time domain GC test.

Suggested Citation

  • Yang, Linghubo & Zhang, Dongxiang, 2013. "Can futures price be a powerful predictor? Frequency domain analysis on Chinese commodity market," Economic Modelling, Elsevier, vol. 35(C), pages 264-271.
    • Handle: RePEc:eee:ecmode:v:35:y:2013:i:c:p:264-271
    DOI: 10.1016/j.econmod.2013.07.011
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    Cited by:

    1. Dai, Yun-Shi & Huynh, Ngoc Quang Anh & Zheng, Qing-Huan & Zhou, Wei-Xing, 2022. "Correlation structure analysis of the global agricultural futures market," Research in International Business and Finance, Elsevier, vol. 61(C).
    2. Mishra, Vinod & Smyth, Russell, 2016. "Are natural gas spot and futures prices predictable?," Economic Modelling, Elsevier, vol. 54(C), pages 178-186.
    3. Kai Liu & Atsushi Koike & Yueying Mu, 2020. "Price Risks and the Lead-Lag Relationship between the Futures and Spot Prices of Soybean, Wheat and Corn," Asian Journal of Economic Modelling, Asian Economic and Social Society, vol. 8(1), pages 76-88, March.

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    More about this item

    Keywords

    Futures price; Spot price; Chinese commodity market; Frequency domain approach; Garbade–Silber Model;
    All these keywords.

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading

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