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.
Download InfoIf you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
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)
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Goodhart, Charles A. E. & O'Hara, Maureen, 1997. "High frequency data in financial markets: Issues and applications," Journal of Empirical Finance, Elsevier, vol. 4(2-3), pages 73-114, June.
- Baillie, R.T. & Bollerslev, T., 1989.
"Intra Day And Inter Market Volatility In Foreign Exchange Rates,"
8811, Michigan State - Econometrics and Economic Theory.
- Baillie, Richard T & Bollerslev, Tim, 1991. "Intra-day and Inter-market Volatility in Foreign Exchange Rates," Review of Economic Studies, Wiley Blackwell, vol. 58(3), pages 565-85, May.
- Ding, Zhuanxin & Granger, Clive W. J. & Engle, Robert F., 1993. "A long memory property of stock market returns and a new model," Journal of Empirical Finance, Elsevier, vol. 1(1), pages 83-106, June.
- Ding, Zhuanxin & Granger, Clive W. J., 1996. "Modeling volatility persistence of speculative returns: A new approach," Journal of Econometrics, Elsevier, vol. 73(1), pages 185-215, July.
- Hyun J. Jin & Darren L. Frechette, 2004. "Fractional Integration in Agricultural Futures Price Volatilities," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 86(2), pages 432-443.
- Baillie, Richard T & Bollerslev, Tim, 2002.
"The Message in Daily Exchange Rates: A Conditional-Variance Tale,"
Journal of Business & Economic Statistics,
American Statistical Association, vol. 20(1), pages 60-68, January.
- Baillie, Richard T & Bollerslev, Tim, 1989. "The Message in Daily Exchange Rates: A Conditional-Variance Tale," Journal of Business & Economic Statistics, American Statistical Association, vol. 7(3), pages 297-305, July.
- Tom Doan, . "RATS program to replicate Baillie and Bollerslev GARCH models with day-of-week effects," Statistical Software Components RTZ00172, Boston College Department of Economics.
- Grané, A. & Veiga, H., 2008. "Accurate minimum capital risk requirements: A comparison of several approaches," Journal of Banking & Finance, Elsevier, vol. 32(11), pages 2482-2492, November.
- Charfeddine Lanouar, 2014. "True or Spurious Long Memory in Volatility : Further Evidence on the Energy Futures Markets," Working Papers 2014-503, Department of Research, Ipag Business School.
- Serpil TURKYILMAZ & Mesut BALIBEY, 2014. "Long Memory Behavior in the Returns of Pakistan Stock Market: ARFIMA-FIGARCH Models," International Journal of Economics and Financial Issues, Econjournals, vol. 4(2), pages 400-410.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Nick Vriend).
If references are entirely missing, you can add them using this form.