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Power ARCH modelling of commodity futures data on the London Metal Exchange

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  • Michael McKenzie
  • Heather Mitchell
  • Robert Brooks
  • Robert Faff

Abstract

A recent addition to the ARCH family of econometric models was introduced by Ding and co-workers wherein the power term by which the data is transformed was estimated within the model rather than being imposed by the researcher. This paper considers the ability of the Power GARCH class of models to capture the stylized features of volatility in a range of commodity futures prices traded on the London Metals Exchange (LME). The results of this procedure suggest that asymmetric effects are not generally present in the LME futures data. Further, unlike stock market data which is well described by the model, futures data is not as well described by the APGARCH model. Nested within the APGARCH model are several other models from the ARCH family. This paper uses the standard log likelihood procedure to conduct pairwise comparisons of the relative merits of each and the results suggest that it is the Taylor GARCH model which performs best.

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Bibliographic Info

Article provided by Taylor & Francis Journals in its journal The European Journal of Finance.

Volume (Year): 7 (2001)
Issue (Month): 1 ()
Pages: 22-38

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Handle: RePEc:taf:eurjfi:v:7:y:2001:i:1:p:22-38

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Keywords: Power Arch London Metal Exchange Futures;

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References

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  1. Brooks, Robert D. & Faff, Robert W. & McKenzie, Michael D. & Mitchell, Heather, 2000. "A multi-country study of power ARCH models and national stock market returns," Journal of International Money and Finance, Elsevier, vol. 19(3), pages 377-397, June.
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Citations

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Cited by:
  1. Ane, Thierry, 2006. "An analysis of the flexibility of Asymmetric Power GARCH models," Computational Statistics & Data Analysis, Elsevier, vol. 51(2), pages 1293-1311, November.
  2. K. Triantafyllopoulos, 2008. "Multivariate stochastic volatility with Bayesian dynamic linear models," Papers 0802.0214, arXiv.org.
  3. Sinha, Pankaj & Mathur, Kritika, 2013. "A study on the Price Behavior of Base Metals traded in India," MPRA Paper 47028, University Library of Munich, Germany.
  4. Tully, Edel & Lucey, Brian M., 2007. "A power GARCH examination of the gold market," Research in International Business and Finance, Elsevier, vol. 21(2), pages 316-325, June.
  5. Triantafyllopoulos, Kostas, 2006. "Multivariate discount weighted regression and local level models," Computational Statistics & Data Analysis, Elsevier, vol. 50(12), pages 3702-3720, August.

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