RT Report
T1 Modelling Long Memory Volatility in Agricultural Commodity Futures Returns
A1 Chang, Chia-Lin
A1 McAleer, Michael
A1 Tansuchat, Roengchai
AB 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.
YR 2012
FD 2012-05
LK https://hdl.handle.net/20.500.14352/49087
UL https://hdl.handle.net/20.500.14352/49087
LA eng
NO 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 ScienceCouncil, Taiwan, and the Japan Society for the Promotion of Science, and the third author acknowledges the Faculty of Economics, Maejo University.
DS Docta Complutense
RD 11 abr 2025