Power ARCH Modelling of Commodity Futures Data on the London Metal Exchange
AbstractA 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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Bibliographic InfoPaper provided by Melbourne - Centre in Finance in its series Papers with number 98-3.
Length: 24 pages
Date of creation: 1998
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ECONOMETRIC MODELS ; EVALUATION ; COMMODITY PRICES;
Other versions of this item:
- Michael McKenzie & Heather Mitchell & Robert Brooks & Robert Faff, 2001. "Power ARCH modelling of commodity futures data on the London Metal Exchange," The European Journal of Finance, Taylor & Francis Journals, vol. 7(1), pages 22-38.
- 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
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