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An empirical evaluation of fat-tailed distributions in modeling financial time series. (English) Zbl 1148.62316
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.
62P05Applications of statistics to actuarial sciences and financial mathematics
62M10Time series, auto-correlation, regression, etc. (statistics)
62F15Bayesian inference
91B84Economic time series analysis
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