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Renewable versus nonrenewable resources: an analysis of volatility in futures prices

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  • Gevorkyan, Arkady

Abstract

This study outlines a new approach for differentiating commodity futures based on their exhaustibility. Various aspects of volatility in the futures prices of renewable resources (palm oil, coffee, soya beans, rice, wheat and corn) and nonrenewable resources (zinc, aluminium, natural gas, gold, crude oil and copper) are studied, exploring whether volatility is greater in the former than in the latter. We use a generalised autoregressive conditional heteroskedasticity (GARCH) model to test our main hypothesis that the volatility in futures prices for renewable resources has recently been equal to or greater than the volatility in futures prices for nonrenewable resources. Our key findings suggest that futures prices for some renewable resources have greater variance than those for benchmark crude oil in a simulated GARCH series. We extend our analysis using a nonlinear vector smooth transition autoregressive (VSTAR) model to test for the existence of a shifting-mean tendency in the commodity series that we researched. We show that transition from a stable to a volatile regime is more abrupt for renewable resources.

Suggested Citation

  • Gevorkyan, Arkady, 2017. "Renewable versus nonrenewable resources: an analysis of volatility in futures prices," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 61(1), January.
    • Handle: RePEc:ags:aareaj:301130
    DOI: 10.22004/ag.econ.301130
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    Cited by:

    1. Elgammal, Mohammed M. & Ahmed, Walid M.A. & Alshami, Abdullah, 2021. "Price and volatility spillovers between global equity, gold, and energy markets prior to and during the COVID-19 pandemic," Resources Policy, Elsevier, vol. 74(C).
    2. Chang, C-L. & McAleer, M.J. & Wang, Y-A., 2018. "Latent Volatility Granger Causality and Spillovers in Renewable Energy and Crude Oil ETFs," Econometric Institute Research Papers TI 2018-052/III, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    3. Zhao, Jing, 2023. "Time-varying impact of geopolitical risk on natural resources prices: Evidence from the hybrid TVP-VAR model with large system," Resources Policy, Elsevier, vol. 82(C).

    More about this item

    Keywords

    Resource /Energy Economics and Policy;

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