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Modelling Long Memory Volatility in Agricultural Commodity Futures Returns



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Chang, Chia-Lin and McAleer, Michael and Tansuchat, Roengchai (2012) Modelling Long Memory Volatility in Agricultural Commodity Futures Returns. [ Documentos de Trabajo del Instituto Complutense de Análisis Económico (ICAE); nº 10, 2012, ] (Unpublished)

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Official URL: http://eprints.ucm.es/15093/



This paper estimates a long memory volatility model for 16 agricultural commodity futures returns from different futures markets, namely corn, oats, soybeans, soybean meal, soybean oil, wheat, live cattle, cattle feeder, pork, cocoa, coffee, cotton, orange juice, Kansas City wheat, rubber, and palm oil. The class of fractional GARCH models, namely the FIGARCH model of Baillie et al. (1996), FIEGARCH model of Bollerslev and Mikkelsen (1996), and FIAPARCH model of Tse (1998), are modelled and compared with the GARCH model of Bollerslev (1986), EGARCH model of Nelson (1991), and APARCH model of Ding et al. (1993). The estimated d parameters, indicating long-term dependence, suggest that fractional integration is found in most of agricultural commodity futures returns series. In addition, the FIGARCH (1,d,1) and FIEGARCH(1,d,1) models are found to outperform their GARCH(1,1) and EGARCH(1,1) counterparts.

Item Type:Working Paper or Technical Report
Additional Information:

For financial support, the first author is most grateful to the National Science Council,
Taiwan, the second author wishes to thank the Australian Research Council, National Science
Council, Taiwan, and the Japan Society for the Promotion of Science, and the third author acknowledges the Faculty of Economics, Maejo University.

Uncontrolled Keywords:Long memory, Agricultural commodity futures, Fractional integration, Asymmetric, Conditional volatility.
Subjects:Social sciences > Economics > Econometrics
JEL:Q14, Q11, Q22, Q51
Series Name:Documentos de Trabajo del Instituto Complutense de Análisis Económico (ICAE)
ID Code:15093
Deposited On:04 May 2012 07:54
Last Modified:17 Jun 2016 09:43

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