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Zbl 1148.62316
So, Mike K.P.; Chen, Cathy W.S.; Lee, Jen-Yu; Chang, Yi-Ping
An empirical evaluation of fat-tailed distributions in modeling financial time series. (English)
[J] Math. Comput. Simul. 77, No. 1, 96-108 (2008). ISSN 0378-4754

Summary: There is substantial evidence that many financial time series exhibit leptokurtosis and volatility clustering. We compare the two most commonly used statistical distributions in empirical analysis to capture these features: the $t$ distribution and the generalized error distribution (GED). A Bayesian approach using a reversible-jump Markov chain Monte Carlo method and a forecasting evaluation method are adopted for the comparison. In the Bayesian evaluation of eight daily market returns, we find that the fitted $t$ error distribution outperforms the GED. In terms of volatility forecasting, models with $t$ innovations also demonstrate superior out-of-sample performance.

MSC 2000:: *62P05 Appl. of statistics to actuarial sciences and financial mathematics
62M10 Time series, etc. (statistics)
62F15 Bayesian inference
91B84 Economic time series analysis

Keywords: Bayesian; GARCH models; generalized error distribution; reversible-jump

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