Abstract
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.
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Curto, J.D., Pinto, J.C. & Tavares, G.N. Modeling stock markets’ volatility using GARCH models with Normal, Student’s t and stable Paretian distributions. Stat Papers 50, 311–321 (2009). https://doi.org/10.1007/s00362-007-0080-5
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DOI: https://doi.org/10.1007/s00362-007-0080-5