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Investor structure and the informational efficiency of commodity futures prices

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  • Chen, Yu-Lun
  • Chang, Ya-Kai

Abstract

This article investigates the impact of the trading positions of hedgers (i.e., producers, merchants, processors, or users of a commodity), speculators (i.e., commodity pool operators, trading advisors, or hedge funds), and swap dealers on the price formation process in the agricultural, metal, and energy futures markets. The hedgers' relative positions exert negative impacts on price efficiency in commodity futures markets. Hedgers are less likely to be information motivated, so their trading delays the price formation process. However, speculators' positions have positive impacts on price efficiency because speculators correct pricing errors. This study also offers evidence that the role of swap dealers, similar to speculators in futures markets, is to provide liquidity and cross-market arbitrage. These findings highlight the role of producers, hedge funds, and swap dealers in price formation processes in commodity futures—information that is beneficial to academics, practitioners, and regulators.

Suggested Citation

  • Chen, Yu-Lun & Chang, Ya-Kai, 2015. "Investor structure and the informational efficiency of commodity futures prices," International Review of Financial Analysis, Elsevier, vol. 42(C), pages 358-367.
    • Handle: RePEc:eee:finana:v:42:y:2015:i:c:p:358-367
    DOI: 10.1016/j.irfa.2015.08.013
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    Cited by:

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    3. Chen, Yu-Lun & Mo, Wan-Shin & Chang, Ya-Kai, 2022. "Investor sentiment spillover effect and market quality in crude oil futures," International Review of Economics & Finance, Elsevier, vol. 82(C), pages 177-193.
    4. Pu, Yingjian & Yang, Baochen, 2022. "The commodity futures' historical basis in trading strategy and portfolio investment," Energy Economics, Elsevier, vol. 105(C).
    5. Bohl, Martin T. & Pütz, Alexander & Sulewski, Christoph, 2021. "Speculation and the informational efficiency of commodity futures markets," Journal of Commodity Markets, Elsevier, vol. 23(C).
    6. Hung, Jui-Cheng & Liu, Hung-Chun & Yang, J. Jimmy, 2021. "Trading activity and price discovery in Bitcoin futures markets," Journal of Empirical Finance, Elsevier, vol. 62(C), pages 107-120.
    7. Fernandez, Viviana, 2017. "A historical perspective of the informational content of commodity futures," Resources Policy, Elsevier, vol. 51(C), pages 135-150.
    8. Ruwei Zhao & Xiong Xiong & Dehua Shen & Wei Zhang, 2019. "Investor Structure and Stock Price Crash Risk in a Continuous Double Auction Market: An Agent-Based Perspective," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 18(02), pages 695-715, March.
    9. Lauter, Tobias & Prokopczuk, Marcel, 2022. "Measuring commodity market quality," Journal of Banking & Finance, Elsevier, vol. 145(C).
    10. Qingbin Gong & Zhe Yang, 2020. "Arbitrage, speculation and futures price fluctuations with boundedly rational and heterogeneous agents," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 15(4), pages 763-791, October.

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    More about this item

    Keywords

    Commodity futures; Hedgers; Pricing error; Speculators; SWAP dealers;
    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
    • E44 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Financial Markets and the Macroeconomy
    • G18 - Financial Economics - - General Financial Markets - - - Government Policy and Regulation

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