The analysis of the techno-economic interactions among the mobile operators and tenants (slices) in the context of 5G network slicing has lately received growing interest by the research community. In particular the problems of admission control, resource allocation/scheduling and pricing for network slicing are not trivial as they affect the profits of the involved stakeholders such as the operator (slice provider) and the network slice owners (tenants or service providers) and therefore the viability of the slice market. Since such problems are entwined, we propose here a novel optimization framework that jointly addresses admission control, resource allocation and pricing. In the proposed framework, the operator owns a fixed amount of resources whereas each slice is characterized by a stochastic demand and utility function reflecting its Quality of Service (QoS) requirements. We have considered two types of slices, one with low traffic profile and deterministic QoS, representing Ultra Reliable Low Latency Communications (URLLC), and one with higher traffic profile and statistical QoS, representing enhanced Mobile BroadBand (eMBB). We devise several models based on whether we allow statistical multiplexing and whether we make use of different prices for different types of slices. We also evaluate the impact of the description of traffic in an aggregate way compared to a detailed one. The outcomes of all variants are analyzed through some numerical experiments which enable us to assess the main flavors of each model.