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Volatility spill-overs in commodity spot prices: New empirical results

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  • Dahl, Christian M.
  • Iglesias, Emma M.

Abstract

The classical rational expectations model of commodity markets implies that expected spot price risk is an explanatory variable in spot price regressions; and also that inventory carryover, which is reduced by a larger price variance, creates autoregressive conditional heteroscedastic processes in spot prices. In order to falsify/verify this theory, it has typically been assumed that the square root of the conditional variance of spot prices, a proxy for spot price risk, enters the conditional mean function of spot prices. Based on this simple representation, a typical but counter intuitive outcome has been that spot price risk has an insignificant impact on spot prices, see, e.g., Beck (Beck, S., 1993. A Rational Expectations Model of Time Varying Risk Premia in Commodities Futures Markets: Theory and Evidence. International Economic Review 34, 149-168, Beck, S., 2001. Autoregressive Conditional Heteroskedasticity in Commodity Spot Prices. Journal of Applied Econometrics 16, 115-132). In this paper, we propose an alternative functional relationship (from GARCH(1,1) to GARCH(1,1)-AR(m)) between spot price risk and spot prices that is fully supported by the classical rational expectations model, and based on this new representation we are able to provide stronger empirical support for Muth's rational expectation theory.

Suggested Citation

  • Dahl, Christian M. & Iglesias, Emma M., 2009. "Volatility spill-overs in commodity spot prices: New empirical results," Economic Modelling, Elsevier, vol. 26(3), pages 601-607, May.
  • Handle: RePEc:eee:ecmode:v:26:y:2009:i:3:p:601-607
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    References listed on IDEAS

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    Cited by:

    1. Amine Lahiani & Duc Khuong Nguyen & Thierry Vo, 2014. "Understanding return and volatility spillovers among major agricultural commodities," Working Papers 2014-243, Department of Research, Ipag Business School.
    2. West, Kenneth D. & Wong, Ka-Fu, 2014. "A factor model for co-movements of commodity prices," Journal of International Money and Finance, Elsevier, vol. 42(C), pages 289-309.
    3. Hegerty, Scott W., 2016. "Commodity-price volatility and macroeconomic spillovers: Evidence from nine emerging markets," The North American Journal of Economics and Finance, Elsevier, vol. 35(C), pages 23-37.
    4. Chkili, Walid & Hammoudeh, Shawkat & Nguyen, Duc Khuong, 2014. "Volatility forecasting and risk management for commodity markets in the presence of asymmetry and long memory," Energy Economics, Elsevier, vol. 41(C), pages 1-18.
    5. Serra, Teresa & Zilberman, David, 2013. "Biofuel-related price transmission literature: A review," Energy Economics, Elsevier, vol. 37(C), pages 141-151.
    6. Walid Chkili, 2015. "Gold–oil prices co-movements and portfolio diversification implications," Economics Bulletin, AccessEcon, vol. 35(4), pages 2832-2845.
    7. Symeonidis, Lazaros & Prokopczuk, Marcel & Brooks, Chris & Lazar, Emese, 2012. "Futures basis, inventory and commodity price volatility: An empirical analysis," Economic Modelling, Elsevier, vol. 29(6), pages 2651-2663.
    8. Chkili, Walid, 2015. "Gold-oil prices co-movements and portfolio diversification implications," MPRA Paper 68110, University Library of Munich, Germany.
    9. Chevallier, Julien, 2010. "Modelling risk premia in CO2 allowances spot and futures prices," Economic Modelling, Elsevier, vol. 27(3), pages 717-729, May.

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