Arbeitspapier

Nonparametric lag selection for time series

A nonparametric version of the Final Prediction Error (FPE) is proposed for lag selection in nonlinear autoregressive time series. We derive its consistency for both local constant and local linear estimators using a derived optimal bandwidth. Further asymptotic analysis suggests a greater probability of overfitting (too many lags) than underfitting (missing important lags). Thus a correction factor is proposed to increase correct fitting by reducing overfitting. Our Monte-Carlo study also corroborates that the correction factor generally improves the probability of correct lag selection for both linear and nonlinear processes. The proposed methods are successfully applied to the Canadian lynx data and daily returns of DM/US-Dollar exchange rates.

Sprache
Englisch

Erschienen in
Series: SFB 373 Discussion Paper ; No. 1997,59

Klassifikation
Wirtschaft
Thema
Consistency
Final Prediction Error
Foreign Exchange Rates
Lag Selection
Nonlinear Autoregression
Nonparametric Method

Ereignis
Geistige Schöpfung
(wer)
Tschernig, Rolf
Yang, Lijian
Ereignis
Veröffentlichung
(wer)
Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes
(wo)
Berlin
(wann)
1997

Handle
URN
urn:nbn:de:kobv:11-10064444
Letzte Aktualisierung
10.03.2025, 11:43 MEZ

Datenpartner

Dieses Objekt wird bereitgestellt von:
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.

Objekttyp

  • Arbeitspapier

Beteiligte

  • Tschernig, Rolf
  • Yang, Lijian
  • Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes

Entstanden

  • 1997

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