Utilize este identificador para referenciar este registo:
https://hdl.handle.net/1822/11073
Título: | Modeling rare events through a pRARMAX process |
Autor(es): | Ferreira, Marta Susana Castro, Luisa Canto e |
Palavras-chave: | Extreme value theory, Max-autoregressive models Classification theory Bayes error |
Data: | 2010 |
Editora: | Elsevier 1 |
Revista: | Journal of Statistical Planning and Inference |
Citação: | "Journal of Statistical Planning and Inference". ISSN 0378-3758. 140:11 (2010) 3552-3566. |
Resumo(s): | Ferreira and Canto e Castro (2007, 2008) introduce a power max-autoregressive process, in short pARMAX, as an alternative to heavy tailed ARMA when modeling rare events. In this paper, an extension of pARMAX is considered, by including a random component which makes the model more applicable to real data. We will see conditions under which this new model, here denoted as pRARMAX, has unique stationary distribution and we analyze its extremal behavior. Based on Bortot and Tawn (1998), we derive a threshold-dependent extremal index which is a functional of the coefficient of tail dependence of Ledford and Tawn (1996, 1997) which in turn relates with the pRARMAX parameter. In order to fit a pRARMAX model to an observed data series, we present a methodology based on minimizing the Bayes risk in classification theory and analyze this procedure through a simulation study. We illustrate with an application to financial data. |
Tipo: | Artigo |
URI: | https://hdl.handle.net/1822/11073 |
DOI: | 10.1016/j.jspi.2010.05.024 |
ISSN: | 0378-3758 |
Versão da editora: | http://www.elsevier.com/wps/find/journaldescription.cws_home/505561/description#description |
Arbitragem científica: | yes |
Acesso: | Acesso restrito UMinho |
Aparece nas coleções: | CMAT - Artigos em revistas com arbitragem / Papers in peer review journals |
Ficheiros deste registo:
Ficheiro | Descrição | Tamanho | Formato | |
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MFer_LCCastro_p.pdf Acesso restrito! | Documento principal | 89,15 kB | Adobe PDF | Ver/Abrir |