Artigo em revista científica Q3
Modeling stock markets' volatility using GARCH models with normal, Student's t and stable Paretian distributions
José Curto (Curto, J.); José Pinto (Pinto, J. C.); Gonçalo Nuno Tavares (Tavares, G. N.);
Título Revista
Statistical Papers
Ano
2009
Língua
Inglês
País
Alemanha
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Abstract/Resumo
As GARCH models and stable Paretian distributions have been revisited in the recent past with the papers of Hansen and Lunde (J Appl Econom 20: 873–889, 2005) and Bidarkota and McCulloch (Quant Finance 4: 256–265, 2004), respectively, in this paper we discuss alternative conditional distributional models for the daily returns of the US, German and Portuguese main stock market indexes, considering ARMA-GARCH models driven by Normal, Student’s t and stable Paretian distributed innovations. We find that a GARCH model with stable Paretian innovations fits returns clearly better than the more popular Normal distribution and slightly better than the Student’s t distribution. However, the Student’s t outperforms the Normal and stable Paretian distributions when the out-of-sample density forecasts are considered.
Agradecimentos/Acknowledgements
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Palavras-chave
Non-Gaussian distributions,Conditional heteroskedasticity
  • Matemáticas - Ciências Naturais