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Evaluating the hedging potential of energy, metals, and agricultural commodities for U.S. stocks post-COVID-19

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  • Han, SeungOh

Abstract

This study employs TVP-VAR analysis to assess risk spillover effects between the U.S. stock ETF and commodity futures (energy, metals, grains, livestock, and soft) during the year surrounding the COVID-19 outbreak. Market connectedness intensifies rapidly after January 2020, with Brent crude oil and heating oil emerging as major net risk transmitters and Richard Bay coal as a primary receiver. While short-term interconnectedness shows sharp spikes with quick reversals, long-term interconnectedness exhibits modest but persistent elevation, necessitating horizon-specific hedging strategies. Our analysis reveals that livestock futures provide the most cost-effective hedge against the S&P 500 ETF, highlighting the potential of previously overlooked instruments. Energy futures demonstrate significant risk mitigation capabilities, reinforcing their established hedging role, while soft futures show notably enhanced hedging effectiveness. These patterns remain consistent across sector ETFs, with metals futures particularly effective for energy ETF hedging. The findings prove robust to alternative specifications, including the NASDAQ 100 ETF, extended analysis periods, different pandemic period definitions, and raw returns.

Suggested Citation

  • Han, SeungOh, 2025. "Evaluating the hedging potential of energy, metals, and agricultural commodities for U.S. stocks post-COVID-19," The North American Journal of Economics and Finance, Elsevier, vol. 77(C).
  • Handle: RePEc:eee:ecofin:v:77:y:2025:i:c:s1062940825000208
    DOI: 10.1016/j.najef.2025.102380
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    More about this item

    Keywords

    COVID-19 outbreak; U.S. stocks; Commodity futures; Risk spillovers; Hedging strategies;
    All these keywords.

    JEL classification:

    • 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
    • G01 - Financial Economics - - General - - - Financial Crises
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • Q43 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Energy and the Macroeconomy

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