Modelling Long Memory Volatility in Agricultural Commodity Futures Returns
AbstractThis paper estimates the 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), FIEGACH 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.
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Bibliographic InfoPaper provided by Center for Advanced Research in Finance, Faculty of Economics, The University of Tokyo in its series CARF F-Series with number CARF-F-183.
Length: 35 pages
Date of creation: Oct 2009
Date of revision:
Other versions of this item:
- CHIA-LIN CHANG & MICHAEL McALEER & ROENGCHAI TANSUCHAT, 2012. "Modelling Long Memory Volatility In Agricultural Commodity Futures Returns," Annals of Financial Economics (AFE), World Scientific Publishing Co. Pte. Ltd., vol. 7(02), pages 1250010-1-1.
- Chang, C-L. & McAleer, M.J. & Tansuchat, R., 2012. "Modelling Long Memory Volatility in Agricultural Commodity Futures Returns," Econometric Institute Research Papers EI 2012-15, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
- Chia-Lin Chang & Michael McAleer & Roengchai Tansuchat, 2012. "Modelling Long Memory Volatility in Agricultural Commodity Futures Returns," Documentos del Instituto Complutense de AnÃ¡lisis EconÃ³mico 2012-10, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, revised May 2012.
- Michael McAleer & Chia-Lin Chang & Roengchai Tansuchat, 2012. "Modelling Long Memory Volatility in Agricultural Commodity Futures Return," KIER Working Papers 817, Kyoto University, Institute of Economic Research.
- Chia-Lin Chang & Michael McAleer & Roengchai Tansuchat, 2012. "Modelling Long Memory Volatility in Agricultural Commodity Futures Returns," Working Papers in Economics 12/09, University of Canterbury, Department of Economics and Finance.
- Roengchai Tansuchat & Chia-Lin Chang & Michael McAleer, 2009. "Modelling Long Memory Volatility in Agricultural Commodity Futures Returns," CIRJE F-Series CIRJE-F-680, CIRJE, Faculty of Economics, University of Tokyo.
- Tansuchat, R. & Chang, C-L. & McAleer, M.J., 2009. "Modelling Long Memory Volatility in Agricultural Commodity Futures Returns," Econometric Institute Research Papers EI 2009-35, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
- C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models &bull Diffusion Processes
- C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
- Q11 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - Aggregate Supply and Demand Analysis; Prices
- Q14 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - Agricultural Finance
This paper has been announced in the following NEP Reports:
- NEP-AGR-2010-09-18 (Agricultural Economics)
- NEP-ALL-2010-09-18 (All new papers)
- NEP-ETS-2010-09-18 (Econometric Time Series)
- NEP-FMK-2010-09-18 (Financial Markets)
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