Bayesian modelling for financial time series with skewness and high kurtosis with the Skew Slash distribution
P. Galeano San Miguel, C. Garcia de la Fuente, M. P. Wiper
Financial data sets often present skewness and high kurtosis. As a consequence, it is natural to look for a model that is flexible enough to capture these characteristics. The proposal is to perform Bayesian inference and prediction for a generalized autoregressive conditional heteroskedastic (GARCH) model, where the innovations are assumed to follow a Skew Slash distribution. Gibbs sampling is used for parameter estimation and volatility prediction, and the method is illustrated using real financial data.
Palabras clave: financial time series, Bayesian analysis, Skew Slash distribution, GARCH model, Skewness, Kurtosis
Programado
XA3 Métodos bayesianos 3
18 de abril de 2012 09:00
Sala Londres
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