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Wavelet Transforms and Commodity Prices

Author

Listed:
  • Connor Jeff

    (Ohio University)

  • Rossiter Rosemary

    (Ohio University)

Abstract

Traders in commodity markets may have different time horizons. This paper uses a scale analysis to investigate heterogeneous trading in such markets. Estimates are presented for price correlations by scale and long memory in the volatility of commodity prices. Wavelet variance is estimated using non-decimated wavelet transforms. Wavelets have the potential to be a useful tool for scale analysis in economics.

Suggested Citation

  • Connor Jeff & Rossiter Rosemary, 2005. "Wavelet Transforms and Commodity Prices," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 9(1), pages 1-22, March.
  • Handle: RePEc:bpj:sndecm:v:9:y:2005:i:1:n:6
    DOI: 10.2202/1558-3708.1170
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    References listed on IDEAS

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    5. Mark J. Jensen, 1997. "Using Wavelets to Obtain a Consistent Ordinary Least Squares Estimator of the Long Memory Parameter," Econometrics 9710002, University Library of Munich, Germany.
    6. James Ramsey, 1999. "Regression over Timescale Decompositions: A Sampling Analysis of Distributional Properties," Economic Systems Research, Taylor & Francis Journals, vol. 11(2), pages 163-184.
    7. Pasquini, Michele & Serva, Maurizio, 1999. "Multiscale behaviour of volatility autocorrelations in a financial market," Economics Letters, Elsevier, vol. 65(3), pages 275-279, December.
    8. Gençay, Ramazan & Dacorogna, Michel & Muller, Ulrich A. & Pictet, Olivier & Olsen, Richard, 2001. "An Introduction to High-Frequency Finance," Elsevier Monographs, Elsevier, edition 1, number 9780122796715, December.
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