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An Approximate Wavelet MLE of Short- and Long-Memory Parameters

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Author Info
Mark Jensen (University of Missouri)

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Abstract

By design a wavelet's strength rests in its ability to localize a process simultaneously in time-scalespace. The wavelet's ability to localize a time series in time-scale space directly leads to the computationalefficiency of the wavelet representation of a N £ N matrix operator by allowing the N largest elements of thewavelet represented operator to represent the matrix operator [Devore, et al. (1992a) and (1992b)]. Thisproperty allows many dense matrices to have sparse representation when transformed by wavelets.In this paper we generalize the long-memory parameter estimator of McCoy and Walden (1996) to estimatesimultaneously the short and long-memory parameters. Using the sparse wavelet representation of a matrixoperator, we are able to approximate an ARFIMA model's likelihood function with the series' wavelet coefficientsand their variances. Maximization of this approximate likelihood function over the short and long-memoryparameter space results in the approximate wavelet maximum likelihood estimates of the ARFIMA model.By simultaneously maximizing the likelihood function over both the short and long-memory parameters andusing only the wavelet coefficient's variances, the approximate wavelet MLE provides a fast alternative to thefrequency-domain MLE. Furthermore, the simulation studies found herein reveal the approximate wavelet MLEto be robust over the invertible parameter region of the ARFIMA model's moving average parameter, whereas thefrequency-domain MLE dramatically deteriorates as the moving average parameter approaches the boundariesof invertibility.

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Publisher Info
Article provided by Berkeley Electronic Press in its journal Studies in Nonlinear Dynamics & Econometrics.

Volume (Year): 3 (1999)
Issue (Month): 4 ()
Pages: 239-253
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Handle: RePEc:bep:sndecm:3:1999:4:239-253

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Related research
Keywords: long memory fractional integration ARFIMA wavelets

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References listed on IDEAS
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.:
  1. James Ramsey & Camille Lampart, 1998. "The Decomposition of Economic Relationships by Time Scale Using Wavelets: Expenditure and Income," Studies in Nonlinear Dynamics & Econometrics, Berkeley Electronic Press, vol. 3(1), pages 23-42. [Downloadable!] (restricted)
  2. Jensen, Mark J., 2000. "An alternative maximum likelihood estimator of long-memory processes using compactly supported wavelets," Journal of Economic Dynamics and Control, Elsevier, vol. 24(3), pages 361-387, March. [Downloadable!] (restricted)
  3. Diebold, Francis X & Rudebusch, Glenn D, 1991. "Is Consumption Too Smooth? Long Memory and the Deaton Paradox," The Review of Economics and Statistics, MIT Press, vol. 73(1), pages 1-9, February. [Downloadable!] (restricted)
    Other versions:
  4. Cheung, Yin-Wong & Diebold, Francis X., 1994. "On maximum likelihood estimation of the differencing parameter of fractionally-integrated noise with unknown mean," Journal of Econometrics, Elsevier, vol. 62(2), pages 301-316, June. [Downloadable!] (restricted)
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  5. 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. [Downloadable!] (restricted)
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  6. Baillie, Richard T & Bollerslev, Tim, 1994. " Cointegration, Fractional Cointegration, and Exchange Rate Dynamics," Journal of Finance, American Finance Association, vol. 49(2), pages 737-45, June. [Downloadable!] (restricted)
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  7. David K. Backus & Stanley E. Zin, 1993. "Long-memory Inflation Uncertainty: Evidence from the Term Structure of Interest Rates," NBER Technical Working Papers 0133, National Bureau of Economic Research, Inc. [Downloadable!] (restricted)
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  8. Ramsey, James B. & Zhang, Zhifeng, 1997. "The analysis of foreign exchange data using waveform dictionaries," Journal of Empirical Finance, Elsevier, vol. 4(4), pages 341-372, December. [Downloadable!] (restricted)
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Cited by:
(explanations, 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.)

  1. Shinn-Juh Lin & Maxwell Stevenson, 2001. "Wavelet Analysis of the Cost-of-Carry Model," Studies in Nonlinear Dynamics & Econometrics, Berkeley Electronic Press, vol. 5(1), pages 87-102. [Downloadable!] (restricted)
  2. James Ramsey, 2002. "Wavelets in Economics and Finance: Past and Future," Studies in Nonlinear Dynamics & Econometrics, Berkeley Electronic Press, vol. 6(3), pages 1090-1090. [Downloadable!] (restricted)
  3. Ramsey, J.B., 2002. "Wavelets in Economics and Finance: Past and Future," Working Papers 02-02, C.V. Starr Center for Applied Economics, New York University. [Downloadable!]
  4. Brandon Whitcher, 2000. "Wavelet-Based Estimation Procedures For Seasonal Long-Memory Models," Computing in Economics and Finance 2000 148, Society for Computational Economics. [Downloadable!]
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