Intraday volatility forecasting: analysis of alternative distributions

Paulo Sérgio Ceretta (), Fernanda Galvão de Barba (), Kelmara Mendes Vieira () and Fernando Casarin ()
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Paulo Sérgio Ceretta: Universidade Federal de Santa Maria

Brazilian Review of Finance, 2011, vol. 9, issue 2, 209-226

Abstract: Volatility forecasting has been of great interest both in academic and professional fields all over the world. However, there is no agreement about the best model to estimatevolatility. New models include measures of skewness, changes of regimes and different distributions; few studies, though, have considered different distributions. This paper aims toinvestigate how the specification of a distribution influences the performance of volatility forecasting on Ibovespa intraday data, using the APARCH model. The forecasts were carriedout assuming six distinct distributions: normal, skewed normal, t-student, skewed t-student, generalized and skewed generalized. The results evidence that the model considering the skewed t-student distribution offered the best fit to the data inside the sample, on the other hand, the model assuming a normal distribution provided a better out-of-the-sample performance forecast.

Keywords: volatility; forecasting models; different distributions (search for similar items in EconPapers)
JEL-codes: C01 C53 G17 (search for similar items in EconPapers)
Date: 2011
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