In this paper we firstly give an introduction to capital market synergetics, a model enabling us to compute transaction costs and investigate the operating efficiency of a stock market's micro structure. Frankfurt's trading system Xetra and NASDAQ are currently implemented at the computer program KapSyn. Secondly, by using KapSyn we examine Xetra's behaviour in different market scenarios, particularly the designated sponsor's performance. The empirical evidence of the KapSyn parameter setting chosen is validated: Connecting the parameter setting to economic data by using neural networks and analytical reasoning underlie the definition of market scenarios. The designated sponsor's eminent importance in non-liquid markets has been demonstrated very impressively. Finally, NASDAQ's transaction cost statistics are investigated in the above scenarios. Compared to Xetra, NASDAQ exhibits minimal transaction costs for mid-size trades, while transaction costs for small and block trades are nearly 100% / 50% higher.