||The thesis focuses on banking regulation and on the nexus between financial sovereign crises. After illustrating the main mechanisms on the recent financial crisis, we construct several multi-agent network models of a financial system for testing its stability under different parameters. In the first part, we focus on the rationale for banking regulation and we describe its development including the recently introduced Basel III measures. The main conclusion of this part is that regulation is to a large extent influenced by the banks and it does not always secure financial system stability. In the second part, we build an agent-based model which enables us to simulate the impacts of various types of negative shocks given various settings of the banking system and the regulatory environment, including the capital and liquidity measures. Our simulations show firstly that sufficient capital buffers are crucial for systemic stability, secondly that the discretionary measures have little effect once a crisis breaks out and thirdly that liquidity measures are a relevant regulatory tool. In the third part, the model is extended so that it allows for testing effects of state support on systemic stability is tested with various parameter settings in Monte Carlo simulations and for testing of feedback loops in which the risk is transferred from the sovereigns back to the financial system. Different parameter settings are tested in Monte Carlo simulations. In the fourth part, the model is calibrated to the real world data using a unique dataset put together from various sources. Our analyses yield the following key results: Firstly, in the short term, all the support measures improve the systemic stability. Secondly, in the longer run, the effects of state support depend on several parameters but still there are settings in which it significantly mitigates the systemic crisis. Finally, there are differences among the effects of the different types of support measures.