The use of GARCH models with stable Paretian innovations in financial modeling has been recently suggested in the literature. This class of processes is attractive because it allows for conditional skewness and leptokurtosis of financial returns without ruling out normality. This contribution illustrates their usefulness in predicting the downside risk of financial assets in the context of modeling foreign exchange-rates and demonstrates their superiority over use of normal or Student´s t GARCH models
This paper addresses the question of the selection of multivariate GARCH models in terms of variance...
This paper analyzes the out-of-sample ability of different parametric and semiparametric GARCH-type ...
Financial returns exhibit conditional heteroscedasticity, asymmetric responses of their volatility t...
Various GARCH models are applied to daily returns of more than 1200 constituents of major stock indi...
Although the GARCH model has been quite successful in capturing important empirical aspects of finan...
It is a well-known fact that financial returns exhibit conditional heteroscedasticity and fat tails....
Most of the Value-at-Risk models assume that financial returns are normally distributed, despite the...
Past financial crises show the importance of adequate risk measurement techniques which adapt more r...
As GARCH models and stable Paretian distributions have been revisited in the recent past with the pa...
A fast method for estimating the parameters of a stable-APARCH not requiring likelihood or iteration...
AbstractGeneralized autoregressive conditional heteroskedasticity (GARCH) models having normal or St...
AbstractIn this article we evaluate the daily conditional volatility and h-step-ahead Value at Risk ...
Various GARCH models are applied to daily returns of more than 1200 constituents of major stock indi...
A new GARCH-type model for autoregressive conditional volatility, skewness, and kurtosis is proposed...
Although the GARCH model has been quite successful in capturing important empirical aspects of finan...
This paper addresses the question of the selection of multivariate GARCH models in terms of variance...
This paper analyzes the out-of-sample ability of different parametric and semiparametric GARCH-type ...
Financial returns exhibit conditional heteroscedasticity, asymmetric responses of their volatility t...
Various GARCH models are applied to daily returns of more than 1200 constituents of major stock indi...
Although the GARCH model has been quite successful in capturing important empirical aspects of finan...
It is a well-known fact that financial returns exhibit conditional heteroscedasticity and fat tails....
Most of the Value-at-Risk models assume that financial returns are normally distributed, despite the...
Past financial crises show the importance of adequate risk measurement techniques which adapt more r...
As GARCH models and stable Paretian distributions have been revisited in the recent past with the pa...
A fast method for estimating the parameters of a stable-APARCH not requiring likelihood or iteration...
AbstractGeneralized autoregressive conditional heteroskedasticity (GARCH) models having normal or St...
AbstractIn this article we evaluate the daily conditional volatility and h-step-ahead Value at Risk ...
Various GARCH models are applied to daily returns of more than 1200 constituents of major stock indi...
A new GARCH-type model for autoregressive conditional volatility, skewness, and kurtosis is proposed...
Although the GARCH model has been quite successful in capturing important empirical aspects of finan...
This paper addresses the question of the selection of multivariate GARCH models in terms of variance...
This paper analyzes the out-of-sample ability of different parametric and semiparametric GARCH-type ...
Financial returns exhibit conditional heteroscedasticity, asymmetric responses of their volatility t...