Complex Event Processing often comes with an enormous amount of event data that needs to be processed. Hence, parallelization plays a significant role in handling high workload situations. The cost of an application however is often defined by the amount of used resources, like in Cloud computing, where the pay-as-you-go model applies. Still, one wants to have a working system that can handle traffic peaks within a given latency bound, so the resources-to-latency-proportion needs to be optimized. Previous work mostly focused on studying complex operator types in specific environments. In this thesis however, we want to get a general view, how parallelization degrees and types influence our CEP system, to be able to estimate what costs could arise. Therefore, a CEP application was created that simulates different system conditions with respect to workload, operator processing time and others, in order to test and analyze the latency properties of a wait operator. This work provides an overview over latency behavior of operators in an example Complex Event Processing application, which can provide a basis for future work in creating an optimized system, that not only keeps a certain latency threshold but also minimizes the costs and resources needed to achieve this goal.