Long memory models for daily and high freouency commodity futures returns

被引:61
作者
Baillie, Richard T. [1 ]
Han, Young-Wook
Myers, Robert J.
Song, Jeongseok
机构
[1] Michigan State Univ, Dept Econ, E Lansing, MI 48824 USA
[2] Michigan State Univ, Dept Finance, E Lansing, MI 48824 USA
[3] Univ London Queen Mary Coll, Dept Econ, London E1 4NS, England
[4] Hallym Univ, Dept Econ, Chunchon, South Korea
[5] Michigan State Univ, Dept Agr Econ, E Lansing, MI 48824 USA
关键词
D O I
10.1002/fut.20267
中图分类号
F8 [财政、金融];
学科分类号
0202 ;
摘要
The volatility of daily futures returns for six important commodities are found to be well described as FIGARCH, fractionally integrated processes, whereas the mean returns exhibit very small departures from the martingale difference property. Several years of high frequency intraday commodity futures returns are also found to have very similar long memory in volatility features as the daily returns. Semiparametric local Whittle estimation of the long memory parameter in absolute returns also finds very significant long memory features. Estimating the long memory parameter across many different data sampling frequencies provides consistent estimates of the long memory parameter, suggesting that the series are self-similar. The results have important implications for empirical work using commodity futures price data. (c) 2007 Wiley Periodicals, Inc.
引用
收藏
页码:643 / 668
页数:26
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