A SIMPLE FRACTIONALLY INTEGRATED MODEL WITH A TIME-VARYING LONG MEMORY PARAMETER Dt
AbstractThis paper generalizes the standard long memory modeling by assuming that the long memory parameter d is stochastic and time varying: we introduce a STAR process on this parameter characterized by a logistic function. We propose an estimation method of this model. Some simulation experiments are conducted. The empirical results suggest that this new model offers an interesting alternative competing framework to describe the persistent dynamics in modelling some financial series.
Download InfoIf you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
Bibliographic InfoPaper provided by HAL in its series Working Papers with number halshs-00275254.
Date of creation: 23 Apr 2008
Date of revision:
Note: View the original document on HAL open archive server: http://halshs.archives-ouvertes.fr/halshs-00275254/en/
Contact details of provider:
Web page: http://hal.archives-ouvertes.fr/
Long-memory; Logistic function; STAR;
You can help add them by filling out this form.
CitEc Project, subscribe to its RSS feed for this item.
- Aloy Marcel & Tong Charles Lai & Peguin-Feissolle Anne & Dufrénot Gilles, 2013.
"A smooth transition long-memory model,"
Studies in Nonlinear Dynamics & Econometrics,
De Gruyter, vol. 17(3), pages 281-296, May.
- Marcel Aloy & Gilles Dufrénot & Charles Lai Tong & Anne Péguin-Feissolle, 2012. "A Smooth Transition Long-Memory Model," AMSE Working Papers 1240, Aix-Marseille School of Economics, Marseille, France, revised Dec 2012.
- Marcel Aloy & Gilles Dufrenot & Charles Lai Tong & Anne Peguin-Feissolle, 2012. "A Smooth Transition Long-Memory Model," Working Papers halshs-00793680, HAL.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (CCSD).
If references are entirely missing, you can add them using this form.