Modelling Long Memory Volatility in Agricultural Commodity Futures Returns
Modelling Long Memory Volatility in Agricultural Commodity Futures Returns
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DOI：
10.2139/ssrn.1491890
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发表时间：
2009-10
期刊：
影响因子：
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通讯作者：
R. Tansuchat;Chia‐Lin Chang;M. McAleer
中科院分区：
文献类型：
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作者：
R. Tansuchat;Chia‐Lin Chang;M. McAleer
This 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.
