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Local polynomial Whittle estimation of perturbed fractional processes

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  • Per Frederiksen
  • Frank S. Nielsen
  • Morten Ørregaard Nielsen

    ()
    (School of Economics and Management, University of Aarhus, Denmark and CREATES)

Abstract

We propose a semiparametric local polynomial Whittle with noise (LPWN) estimator of the memory parameter in long memory time series perturbed by a noise term which may be serially correlated. The estimator approximates the spectrum of the perturbation as well as that of the short-memory component of the signal by two separate polynomials. Furthermore, an empirical investigation of the 30 DJIA stocks shows that this estimator indicates stronger persistence in volatility than the standard local Whittle estimator.

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Bibliographic Info

Paper provided by School of Economics and Management, University of Aarhus in its series CREATES Research Papers with number 2008-29.

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Length: 47
Date of creation: 09 Jun 2008
Date of revision:
Handle: RePEc:aah:create:2008-29

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Web page: http://www.econ.au.dk/afn/

Related research

Keywords: Bias reduction; local Whittle; long memory; perturbed fractional process; semiparametric estimation; stochastic volatility;

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References

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  1. Donald W.K. Andrews & Patrik Guggenberger, 2000. "A Bias-Reduced Log-Periodogram Regression Estimator for the Long-Memory Parameter," Cowles Foundation Discussion Papers 1263, Cowles Foundation for Research in Economics, Yale University.
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  4. Per Frederiksen & Morten Orregaard Nielsen, 2008. "Bias-Reduced Estimation of Long-Memory Stochastic Volatility," Journal of Financial Econometrics, Society for Financial Econometrics, vol. 6(4), pages 496-512, Fall.
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  20. Arteche, Josu, 2004. "Gaussian semiparametric estimation in long memory in stochastic volatility and signal plus noise models," Journal of Econometrics, Elsevier, vol. 119(1), pages 131-154, March.
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  24. Bollerslev, Tim & Jubinski, Dan, 1999. "Equity Trading Volume and Volatility: Latent Information Arrivals and Common Long-Run Dependencies," Journal of Business & Economic Statistics, American Statistical Association, vol. 17(1), pages 9-21, January.
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Citations

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Cited by:
  1. Mccloskey, Adam & Perron, Pierre, 2013. "Memory Parameter Estimation In The Presence Of Level Shifts And Deterministic Trends," Econometric Theory, Cambridge University Press, vol. 29(06), pages 1196-1237, December.
  2. Eduardo Rossi & Paolo Santucci de Magistris, 2011. "Estimation of long memory in integrated variance," CREATES Research Papers 2011-11, School of Economics and Management, University of Aarhus.
  3. Per Frederiksen & Morten Ørregaard Nielsen, 2008. "Bias-reduced estimation of long memory stochastic volatility," CREATES Research Papers 2008-35, School of Economics and Management, University of Aarhus.
  4. Per Frederiksen & Frank S. Nielsen, 2008. "Estimation of Dynamic Models with Nonparametric Simulated Maximum Likelihood," CREATES Research Papers 2008-59, School of Economics and Management, University of Aarhus.
  5. Frank S. Nielsen, 2008. "Local polynomial Whittle estimation covering non-stationary fractional processes," CREATES Research Papers 2008-28, School of Economics and Management, University of Aarhus.

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