Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/158552
Authors: 
Caivano, Michele
Harvey, Andrew
Luati, Alessandra
Year of Publication: 
2016
Citation: 
[Journal:] SERIEs - Journal of the Spanish Economic Association [ISSN:] 1869-4195 [Volume:] 7 [Year:] 2016 [Issue:] 1 [Pages:] 99-120
Abstract: 
We describe observation driven time series models for Student-t and EGB2 conditional distributions in which the signal is a linear function of past values of the score of the conditional distribution. These specifications produce models that are easy to implement and deal with outliers by what amounts to a soft form of trimming in the case of t and a soft form of Winsorizing in the case of EGB2. We show how a model with trend and seasonal components can be used as the basis for a seasonal adjustment procedure. The methods are illustrated with US and Spanish data.
Subjects: 
Fat tails
EGB2
Score
Robustness
Student's t
Trimming
Winsorizing
JEL: 
C22
G17
Persistent Identifier of the first edition: 
Creative Commons License: 
http://creativecommons.org/licenses/by/4.0/
Document Type: 
Article

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