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<p>This study examines how commodity financialization—marked by surging capital inflows and new financial instruments like ETFs—affects commodity pricing dynamics by analyzing inventory-linked convenience yield and investor behavior. Based on the extended theory of storage, using futures market data from 1994 to 2021, this paper examines the efficiency of the factor models in capturing financialization in commodity markets. Furthermore, Fama-MacBeth regression, structural vector autoregressive (SVAR) model, and several statistical indicators are adopted to illustrate the roles of heterogeneous investor behavior in explaining and forecasting commodity pricing. The empirical results can be summarized as follows. Firstly, a financialization-inclusive two-factor model outperforms a single-factor model in aligning with actual commodity futures prices and their term structure. Secondly, non-commercial traders dominate trend-following trades, while commercial traders dominate counter-trend trades. Thirdly, heterogeneous investors’ positions have both short- and long-term predictive effects on commodity prices. In summary, this paper demonstrates the importance of investor behavior for commodity pricing and provides policymakers with regulatory insights.</p>

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The predictive effect of heterogeneous investor behavior on commodity pricing

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年4月6日

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  • Hang Shao,
  • Zhou Li

摘要

This study examines how commodity financialization—marked by surging capital inflows and new financial instruments like ETFs—affects commodity pricing dynamics by analyzing inventory-linked convenience yield and investor behavior. Based on the extended theory of storage, using futures market data from 1994 to 2021, this paper examines the efficiency of the factor models in capturing financialization in commodity markets. Furthermore, Fama-MacBeth regression, structural vector autoregressive (SVAR) model, and several statistical indicators are adopted to illustrate the roles of heterogeneous investor behavior in explaining and forecasting commodity pricing. The empirical results can be summarized as follows. Firstly, a financialization-inclusive two-factor model outperforms a single-factor model in aligning with actual commodity futures prices and their term structure. Secondly, non-commercial traders dominate trend-following trades, while commercial traders dominate counter-trend trades. Thirdly, heterogeneous investors’ positions have both short- and long-term predictive effects on commodity prices. In summary, this paper demonstrates the importance of investor behavior for commodity pricing and provides policymakers with regulatory insights.