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On robust local polynomial estimation with long-memory errors

  • Jan Beran

    ()

    (Center of Finance and Econometrics)

  • Yuanhua Feng

    ()

    (Center of Finance and Econometrics)

  • Sucharita Gosh

    (Landscape Department, Swiss Federal Research Institute WSL)

  • Philipp Sibbertsen

    (Fachbereich Statistik, Universität Dortmund)

Prediction in time series models with a trend requires reliable estima- tion of the trend function at the right end of the observed series. Local polynomial smoothing is a suitable tool because boundary corrections are included implicitly. However, outliers may lead to unreliable estimates, if least squares regression is used. In this paper, local polynomial smoothing based on M-estimators are asymptotically equivalent to the least square solution, under the (ideal) Gaussian model. Outliers turn out to have a major effect on nonrobust bandwidht selection, in particular due to the change of the dependence structure.

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Paper provided by Center of Finance and Econometrics, University of Konstanz in its series CoFE Discussion Paper with number 00-18.

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Length: 17 Pages
Date of creation: Jun 2000
Date of revision:
Handle: RePEc:knz:cofedp:0018
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  1. Jan Beran & Yuanhua Feng, 2000. "Data-driven estimation of semiparametric fractional autoregressive models," CoFE Discussion Paper 00-16, Center of Finance and Econometrics, University of Konstanz.
  2. Jan Beran & Dirk Ocker, 1999. "SEMIFAR Forecasts, with Applications to Foreign Exchange Rates," CoFE Discussion Paper 99-13, Center of Finance and Econometrics, University of Konstanz.
  3. Giraitis, Liudas & Koul, Hira L. & Surgailis, Donatas, 1996. "Asymptotic normality of regression estimators with long memory errors," Statistics & Probability Letters, Elsevier, vol. 29(4), pages 317-335, September.
  4. Jan Beran & Sucharita Gosh & Philipp Sibbertsen, 2000. "Nonparametric M-Estimation with Long-Memory Errors," CoFE Discussion Paper 00-19, Center of Finance and Econometrics, University of Konstanz.
  5. Jan Beran & Yuanhua Feng, 2002. "Local Polynomial Fitting with Long-Memory, Short-Memory and Antipersistent Errors," Annals of the Institute of Statistical Mathematics, Springer, vol. 54(2), pages 291-311, June.
  6. Jan Beran, 1999. "SEMIFAR Models - A Semiparametric Framework for Modelling Trends, Long Range Dependence and Nonstationarity," CoFE Discussion Paper 99-16, Center of Finance and Econometrics, University of Konstanz.
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