The aim of the paper is to improve the Lee-Carter model performance developing a methodology able to refine its predictive accuracy. Considering relevant information the discrepancies between the real data and the Lee-Carter outputs, we model a measure of the fitting errors as a Cox-Ingersoll-Ross process. A new LC model is derived, called mLC. We apply the results over a fixed prediction span and with respect to the mortality data relating to the Italian females aged 18 and 65, chosen as examples of the model application. Through the backtesting procedure within a static framework, the model mLC proves itself to outperform the LC model.

Improving Lee-Carter forecasting: methodology and some results / Apicella, Giovanna; Dacorogna, Michel M.; Di Lorenzo, Emilia; Sibillo, Marilena. - STAMPA. - (2018), pp. 57-61. [10.1007/978-3-319-89824-7_10].

Improving Lee-Carter forecasting: methodology and some results

Apicella, Giovanna
;
2018

Abstract

The aim of the paper is to improve the Lee-Carter model performance developing a methodology able to refine its predictive accuracy. Considering relevant information the discrepancies between the real data and the Lee-Carter outputs, we model a measure of the fitting errors as a Cox-Ingersoll-Ross process. A new LC model is derived, called mLC. We apply the results over a fixed prediction span and with respect to the mortality data relating to the Italian females aged 18 and 65, chosen as examples of the model application. Through the backtesting procedure within a static framework, the model mLC proves itself to outperform the LC model.
2018
Mathematical and Statistical Methods for Actuarial Sciences and Finance
978-3-319-89823-0
978-3-319-89824-7
backtesting methods; Cox-Ingersoll-Ross process; Lee-Carter model; out-of-sample forecasting performance
02 Pubblicazione su volume::02a Capitolo o Articolo
Improving Lee-Carter forecasting: methodology and some results / Apicella, Giovanna; Dacorogna, Michel M.; Di Lorenzo, Emilia; Sibillo, Marilena. - STAMPA. - (2018), pp. 57-61. [10.1007/978-3-319-89824-7_10].
File allegati a questo prodotto
File Dimensione Formato  
Apicella_Improving_2018.pdf

solo gestori archivio

Note: https://link.springer.com/chapter/10.1007/978-3-319-89824-7_10
Tipologia: Documento in Post-print (versione successiva alla peer review e accettata per la pubblicazione)
Licenza: Tutti i diritti riservati (All rights reserved)
Dimensione 76.01 kB
Formato Adobe PDF
76.01 kB Adobe PDF   Contatta l'autore
Apicella_Improving_2018.pdf

solo gestori archivio

Note: https://www.springer.com/us/book/9783319898230#aboutBook
Tipologia: Versione editoriale (versione pubblicata con il layout dell'editore)
Licenza: Tutti i diritti riservati (All rights reserved)
Dimensione 94.28 kB
Formato Adobe PDF
94.28 kB Adobe PDF   Contatta l'autore

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/11573/1135459
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 0
  • ???jsp.display-item.citation.isi??? ND
social impact