Cogarch models: A statistical application

One of the reason that suggests to use COGARCH models to fit financial log-return data is due to the fact that they are able to capture the so called stylized facts observed in real data: uncorrelated log-returns but correlated absolute log-return, time varying volatility, conditional heteroscedasticity, cluster in volatility, heavy tailed and asymmetric unconditional distributions, leverage effects. The aims of this paper is to fit the COGARCH models to a real financial data set, estimate the parameters of the models via the prediction based estimating functions and to look at the performance of these estimates.