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Faculty of Economics

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Caivano, M., Harvey, A. C. and Luati, A.

Robust time series models with trend and seasonal components

SERIEs : Journal of the Spanish Economic Association

pp. 99-120 (2016)

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.

Keywords: Fat tails, EGB2, Score, Robustness, Student's t, Trimming, Winsorizing

JEL Codes: C22, G17

Author links: Andrew Harvey  

Publisher's Link: http://link.springer.com/10.1007/s13209-015-0134-1

Keynes Fund Project(s):
Dynamic Models for Volatility and Heavy Tails (JHLC)  
Dynamic Models for Volatility and Heavy Tails (JHLH)  



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