Long Memory and FIGARCH Models for Daily and High Frequency Commodity Prices
AbstractDaily 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.
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Bibliographic InfoPaper provided by Queen Mary, University of London, School of Economics and Finance in its series Working Papers with number 594.
Date of creation: Apr 2007
Date of revision:
Commodity returns; Futures markets; Long memory; FIGARCH;
Find related papers by JEL classification:
- C4 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics
- C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models &bull Diffusion Processes
This paper has been announced in the following NEP Reports:
- NEP-ALL-2007-04-09 (All new papers)
- NEP-ECM-2007-04-09 (Econometrics)
- NEP-ETS-2007-04-09 (Econometric Time Series)
- NEP-MST-2007-04-09 (Market Microstructure)
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