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Both unconditional mixed-normal distributions and GARCH models with fat-tailed conditional distributions have been employed for modeling financial return data. We consider a mixed-normal distribution coupled with a GARCH-type structure which allows for conditional variance in each of the...
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A fast method is developed for value at risk and expected shortfall prediction for univariate asset return time series exhibiting leptokurtosis, asymmetry, and conditional heteroskedasticity. It is based on a GARCH-type process driven by noncentral t innovations. While the method involves use of...
Persistent link: https://www.econbiz.de/10010412665
A fast method is developed for value-at-risk and expected shortfall prediction for univariate asset return time series exhibiting leptokurtosis, asymmetry and conditional heteroskedasticity. It is based on a GARCH-type process driven by noncentral t innovations. While the method involves the use...
Persistent link: https://www.econbiz.de/10010429763
We investigate alternative unconditional and conditional distributional models for the returns on Japan's Nikkei 225 stock market index. Among them is the recently introduced class of ARMA-GARCH models driven by α-stable (or stable Paretian) distributed innovations, designed to capture the...
Persistent link: https://www.econbiz.de/10005727051
Both unconditional mixed-normal distributions and GARCH models with fat-tailed conditional distributions have been employed for modeling financial return data. We consider a mixed-normal distribution coupled with a GARCH-type structure which allows for conditional variance in each of the...
Persistent link: https://www.econbiz.de/10010317385
While much of classical statistical analysis is based on Gaussian distributional assumptions, statistical modeling with the Laplace distribution has gained importance in many applied fields. This phenomenon is rooted in the fact that, like the Gaussian, the Laplace distribution has many...
Persistent link: https://www.econbiz.de/10010298301