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Analyzing Strongly Periodic Series in the Frequency Domain: A Comparison of Alternative Approaches with Applications

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  • Artis, Michael J
  • Clavel, Jose Garcia
  • Hoffmann, Mathias
  • Nachane, Dilip M

Abstract

Strongly periodic series occur frequently in many disciplines. This paper reviews one specific approach to analyzing such series viz. the harmonic regression approach. In this paper, the five major methods suggested under this approach are critically reviewed and compared, and their empirical potential highlighted via two applications. The out-of-sample forecast comparisons are made using the Superior Predictive Ability test, which specifically guards against the perils of data snooping. Certain tentative conclusions are drawn regarding the relative forecasting ability of the different methods.

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Paper provided by C.E.P.R. Discussion Papers in its series CEPR Discussion Papers with number 6517.

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Date of creation: Oct 2007
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Handle: RePEc:cpr:ceprdp:6517

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Related research

Keywords: autoregressive methods; data snooping; dynamic harmonic regression; eigenvalue methods; mixed spectrum; multiple forecast comparisons;

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  1. Halbert White, 2000. "A Reality Check for Data Snooping," Econometrica, Econometric Society, vol. 68(5), pages 1097-1126, September.
  2. Ghysels,Eric & Osborn,Denise R., 2001. "The Econometric Analysis of Seasonal Time Series," Cambridge Books, Cambridge University Press, number 9780521565882, December.
  3. Kenneth D. West, 1994. "Asymptotic Inference About Predictive Ability," Macroeconomics 9410002, EconWPA.
  4. Peter Young, 1999. "Recursive and en-bloc approaches to signal extraction," Journal of Applied Statistics, Taylor & Francis Journals, vol. 26(1), pages 103-128.
  5. Peter Reinhard Hansen, 2001. "An Unbiased and Powerful Test for Superior Predictive Ability," Working Papers 2001-06, Brown University, Department of Economics.
  6. Asger Lunde & Peter Reinhard Hansen, 2001. "A Forecast Comparison of Volatility Models: Does Anything Beat a GARCH(1,1)?," Working Papers 2001-04, Brown University, Department of Economics.
  7. Pesaran, M.H. & Timmermann, A., 1990. "A Simple Non-Parametric Test Of Predictive Performance," Papers 29, California Los Angeles - Applied Econometrics.
  8. Francis X. Diebold & Robert S. Mariano, 1994. "Comparing Predictive Accuracy," NBER Technical Working Papers 0169, National Bureau of Economic Research, Inc.
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