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Autoregressive conditional heteroscedasticity in commodity spot prices

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  • Stacie Beck

    (Department of Economics, University of Delaware, Newark, DE 19716, USA)

Abstract

Muth's (1961) rational expectations model of commodity markets implies that inventory carryover creates ARCH processes in prices. The model also indicates that the expected price variance is an explanatory variable in price regressions. Hypotheses were tested on price data of twenty commodities using a variation of Engle et al. (1987) ARCH-M technique. An ARCH process was found in storable and not in non-storable commodity data, as expected. However, changes in expected price variance have no significant impact on price. Copyright © 2001 John Wiley & Sons, Ltd.

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Bibliographic Info

Article provided by John Wiley & Sons, Ltd. in its journal Journal of Applied Econometrics.

Volume (Year): 16 (2001)
Issue (Month): 2 ()
Pages: 115-132

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Handle: RePEc:jae:japmet:v:16:y:2001:i:2:p:115-132

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  1. Zivot, Eric & Andrews, Donald W K, 2002. "Further Evidence on the Great Crash, the Oil-Price Shock, and the Unit-Root Hypothesis," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(1), pages 25-44, January.
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Cited by:
  1. Laure Bamière & Vincent Martinet & Christophe Gouel, 2013. "Stochastic viability of second generation biofuel chains: Micro-economic spatial modeling in France," Working Papers 2013/02, INRA, Economie Publique.
  2. Jean-Thomas Bernard & Lynda Khalaf & Maral Kichian & Sebastien McMahon, 2006. "Forecasting Commodity Prices: GARCH, Jumps, and Mean Reversion," Working Papers 06-14, Bank of Canada.
  3. Byrne, Joseph P. & Fazio, Giorgio & Fiess, Norbert, 2011. "Primary commodity prices : co-movements, common factors and fundamentals," Policy Research Working Paper Series 5578, The World Bank.
  4. He, Dequan & Holt, Matthew T., 2004. "Efficiency Of Forest Commodity Futures Markets," 2004 Annual meeting, August 1-4, Denver, CO 20344, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
  5. de Nicola, Francesca & De Pace, Pierangelo & Hernandez, Manuel A., 2014. "Co-movement of major commodity price returns : time-series assessment," Policy Research Working Paper Series 6845, The World Bank.
  6. Kilima, Fredy & Chung, Chanjin & Kenkel, Philip L. & Mbiha, Emanuel, 2004. "The Impact Of Market Reforms On Spatial Volatility Of Maize Price In Tanzania," 2004 Annual meeting, August 1-4, Denver, CO 20332, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
  7. Bernard, Jean-Thomas & Khalaf, Lynda & Kichian, Maral & McMahon, Sébastien, 2008. "Oil Prices: Heavy Tails, Mean Reversion and the Convenience Yield," Cahiers de recherche 0801, GREEN.
  8. Serra, Teresa & Zilberman, David, 2013. "Biofuel-related price transmission literature: A review," Energy Economics, Elsevier, vol. 37(C), pages 141-151.
  9. Hafedh Bouakez & Badye Omar Essid & Michel Normandin, 2010. "Stock Returns and Monetary Policy: Are There Any Ties ?," Cahiers de recherche 1026, CIRPEE.
  10. Power, Gabriel J. & Turvey, Calum G., 2010. "Long-range dependence in the volatility of commodity futures prices: Wavelet-based evidence," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(1), pages 79-90.
  11. Ederington, Louis H. & Guan, Wei, 2013. "The cross-sectional relation between conditional heteroskedasticity, the implied volatility smile, and the variance risk premium," Journal of Banking & Finance, Elsevier, vol. 37(9), pages 3388-3400.
  12. 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.
  13. Casson, Catherine & Fry, J. M., 2011. "Revolutionary change and structural breaks: A time series analysis of wages and commodity prices in Britain 1264-1913," MPRA Paper 27866, University Library of Munich, Germany.
  14. Lee, Yen-Hsien & Hu, Hsu-Ning & Chiou, Jer-Shiou, 2010. "Jump dynamics with structural breaks for crude oil prices," Energy Economics, Elsevier, vol. 32(2), pages 343-350, March.

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