131121 20240205173707.0 doi 10.1080/13504851.2012.669454 sideral 77186 ART-2012-77186 eng Alda, Mercedes Universidad de Zaragoza (orcid)0000-0002-2525-9049 Linear and nonlinear financial time series: Evidence in a sample of pension funds in Spain and the United Kingdom 2012 In this article, we examine whether traditional linear models are suitable to assess financial samples, because financial data usually present nonnormality or nonlinear patterns, therefore linear models do not always adequately capture them. For this reason, as returns series usually follow autoregressive patterns, nonlinear models such as Self-Exciting Threshold Autoregressive (SETAR), Logistic STAR (LSTAR), Additive Autoregressive (AAR) or Neural Network (NNET) could provide a good fit. We study whether two samples of pension funds' returns in Spain and the United Kingdom present these features, and we find that the most appropriate model for the Spanish sample is an autoregressive model, but in the United Kingdom sample, we fit a neural network. info:eu-repo/semantics/closedAccess by-nc-nd http://creativecommons.org/licenses/by-nc-nd/3.0/es/ 0.295 2012 ECONOMICS 273 / 333 = 0.82 2012 Q4 T3 info:eu-repo/semantics/article info:eu-repo/semantics/acceptedVersion Ferruz, Luis Universidad de Zaragoza (orcid)0000-0002-3816-9747 4002 230 Universidad de Zaragoza Dpto. Contabilidad y Finanzas Área Economía Finan. y Contab. 19, 18 (2012), 1933-1937 Appl. econ. lett. APPLIED ECONOMICS LETTERS 1350-4851 93945 http://zaguan.unizar.es/record/131121/files/texto_completo.pdf Postprint 1910770 http://zaguan.unizar.es/record/131121/files/texto_completo.jpg?subformat=icon icon Postprint oai:zaguan.unizar.es:131121 articulos driver 2024-02-05-15:06:35 ARTICLE