The finite sample properties of the state space methods applied to long memory time series are analyzed through Monte Carlo simulations. The state space setup allows to introduce a novel modeling approach in the long memory framework, which directly tackles measurement errors and random level shifts. Missing values and several alternative sources of misspecification are also considered. It emerges that the state space methodology provides a valuable alternative for the estimation of the long memory models, under different data generating processes, which are common in financial and economic series. Two empirical applications highlight the practical usefulness of the proposed state space methods.

When long memory meets the Kalman filter: a comparative study / Grassi, Stefano; De Magistris, Paolo Santucci. - In: COMPUTATIONAL STATISTICS & DATA ANALYSIS. - ISSN 0167-9473. - 76:(2014), pp. 301-319. [10.1016/j.csda.2012.10.018]

When long memory meets the Kalman filter: a comparative study

Grassi, Stefano;De Magistris, Paolo Santucci
2014

Abstract

The finite sample properties of the state space methods applied to long memory time series are analyzed through Monte Carlo simulations. The state space setup allows to introduce a novel modeling approach in the long memory framework, which directly tackles measurement errors and random level shifts. Missing values and several alternative sources of misspecification are also considered. It emerges that the state space methodology provides a valuable alternative for the estimation of the long memory models, under different data generating processes, which are common in financial and economic series. Two empirical applications highlight the practical usefulness of the proposed state space methods.
ARFIMA modelsState spaceMissing observationsMeasurement errorLevel shifts
When long memory meets the Kalman filter: a comparative study / Grassi, Stefano; De Magistris, Paolo Santucci. - In: COMPUTATIONAL STATISTICS & DATA ANALYSIS. - ISSN 0167-9473. - 76:(2014), pp. 301-319. [10.1016/j.csda.2012.10.018]
File in questo prodotto:
File Dimensione Formato  
Grassi_Santucci_2014.pdf

Solo gestori archivio

Tipologia: Documento in Post-print
Licenza: Tutti i diritti riservati
Dimensione 550.68 kB
Formato Adobe PDF
550.68 kB Adobe PDF   Visualizza/Apri
Pubblicazioni consigliate

Caricamento pubblicazioni consigliate

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11385/178213
Citazioni
  • Scopus 13
  • ???jsp.display-item.citation.isi??? 14
social impact