Using high frequency data for European stock market returns, previous research (Acatrinei et. al. 2011) revealed that the outliers of these returns (computed as returns situated outside of the 95% confidence interval) tend to be simultaneous. This can be considered as support for the hypothesis that the stock markets tend to be correlated at the high frequency level. This paper proposes a modeling of these type of interactions by analyzing the characteristics of the dynamic coefficients of correlations between pairs of a series of 14 stock market index returns (DAX (Germany), CAC (France), UKX (UK), IBEX (Spain,), SMI (Switzerland), FTSEMIB (Italy), PSI20 (Portugal) ISEQ (Ireland), ATX (Austria), WIG (Poland), PX (Czech Republic), BUX (Hungary), BET (Romania) and SBITOP (Slovenia) built in a common sample) computed at the. five-minute frequency. An analysis of the outliers for each series of correlations is performed. The calibration will be realized for different frequencies, starting from five-minute and going to daily returns, aiming at capturing the proper frequency for each model, as well as providing a perspective of the time scale structure of the correlations.