Long Memory and FIGARCH Models for Daily and High Frequency Commodity Prices

Richard T. Baillie, Young-Wook Han, Robert J. Myers and Jeongseok Song
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Richard T. Baillie: Michigan State University and Queen Mary, University of London
Young-Wook Han: Hallym University, Chunchon
Robert J. Myers: Michigan State University
Jeongseok Song: Chung-Ang University, Seoul

No 594, Working Papers from Queen Mary University of London, School of Economics and Finance

Abstract: Daily futures returns on six important commodities are found to be well described as FIGARCH fractionally integrated volatility processes, with small departures from the martingale in mean property. The paper also analyzes several years of high frequency intra day commodity futures returns and finds very similar long memory in volatility features at this higher frequency level. Semi parametric Local Whittle estimation of the long memory parameter supports the conclusions. 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 future empirical work using commodity price and returns data.

Keywords: Commodity returns; Futures markets; Long memory; FIGARCH (search for similar items in EconPapers)
JEL-codes: C22 C4 (search for similar items in EconPapers)
Date: 2007-04-01
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Citations: View citations in EconPapers (66)

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Persistent link: https://EconPapers.repec.org/RePEc:qmw:qmwecw:594

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