A recent addition to the ARCH family of econometric models was introduced by Ding, Granger and Engle (1993) 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 stylised features of volatility in a range of commodity futures prices traded on the London Metals Exchange. 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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Paper provided by Melbourne - Centre in Finance in its series Papers with number
98-3.
Length: 24 pages Date of creation: 1998 Date of revision: Handle: RePEc:fth:melrfi:98-3
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Find related papers by JEL classification: C50 - Mathematical and Quantitative Methods - - Econometric Modeling - - - General C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation O13 - Economic Development, Technological Change, and Growth - - Economic Development - - - Agriculture; Natural Resources; Environment; Other Primary Products
References listed on IDEAS Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
Higgins, Matthew L & Bera, Anil K, 1992.
"A Class of Nonlinear ARCH Models,"
International Economic Review,
Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 33(1), pages 137-58, February.
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