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In this study, the modified pseudo-Gaussian copula function is considered together with marginal gamma and Poisson generalized linear models and a modified pseudo-copula regression model is proposed to model dependency between claim severity and frequency. With the pseudo-copula, close estimates to the real values were found, and flexible dependency modelling is presented with the modified correlation coefficients according to the dependence between the claim severity and frequency of different risk groups. The pseudo-maximization by parts method was used for parameter estimation by developing the maximization by parts algorithm. The proposed model was analyzed with both simulation and real data analysis. Under the assumption of independence and when dependency is taken into account, the mean square errors of the parameter estimates according to different modifications were calculated and compared. The parameters estimated by the modified pseudo-copula regression model have lower errors than the estimates found using the model with fixed correlation coefficient and the model under the independence assumption. Finally, the models were compared and it was observed that the proposed model gives better results. [ABSTRACT FROM AUTHOR]

The extreme values in financial markets have been investigated in this study by using two different methods of extreme value theory: block maxima method and peaks over threshold method. Value at Risk, expected shortfall and return level are the risk tools that are taken benefit for risk analysis. Risks of an investor that has a position on IMKB-100 return index have been analyzed by measuring risk values for different percentages and performances of the methods have been compared. [ABSTRACT FROM AUTHOR]