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Title: Study of the banking system's stability using control theory
Author: Wei, Mengyang
ISNI:       0000 0004 6349 2989
Awarding Body: University of Kent
Current Institution: University of Kent
Date of Award: 2017
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The 2007-2009 financial meltdown reflected the failure of the regulators to address financial fragility and it has clearly showed that regulating banks on an individual basis was an ineffective approach to prevent financial crises. Before the crisis, financial regulation was primarily focused on managing the risk of individual banks by requiring them to keep sufficient reserves to safeguard themselves from the inherent risk of their own investments. Since they ignored the risks that are generated by links between the banks, i.e. interbank borrowing and lending, a failure in a small number of banks could spread to other banks, and cause the paralysis of the whole banking system. Therefore, there is the need to give special emphasis to systemic risk, rather than consider the risk at an individual level. From an academic research point of view, the 2007-2009 financial crisis renewed the interest in finding new ways of studying financial systems. More specifically, since then new modelling frameworks have been proposed that incorporate the interconnected nature of the banking system. Network models have been used to investigate the stability of the banking system under different conditions, e.g. different banks' size and connectivity. This thesis proposes a new dynamic network model based on ordinary differential equations, which represents the banking system and seeks to interface the network model approach with control engineering. Control theory is an interdisciplinary branch of engineering, which is used to study the behaviour of dynamical systems, and how their behaviour can be modified by feedback mechanisms to achieve a desirable performance. In this work control theory is applied for the first time to analyse a model of the banking system and to propose feedback mechanisms, which preserve the stability of the system and that can ultimately inform financial regulators.
Supervisor: Marcelli, Gianluca ; León-Ledesma, Miguel ; Spurgeon, Sarah Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available