Thesis
Mathematical modelling, scenario simulation and policy analysis
- Abstract:
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Scenario simulation and stress testing have become indispensable tools for policy makers for the monitoring and management of risk in complex socio-economic systems with heterogeneous, interrelated components. This thesis contains several methodological contributions to this increasingly important field at the intersection of mathematical modelling and policy, with applications focusing on three specific areas: the stress testing of large financial institutions, the financial stability of the UK reinsurance sector and the analysis of control policies for the COVID-19 pandemic in England.
Chapter 2 proposes a new framework for the joint stress testing of liquidity and solvency risk for financial institutions. Rather than being specified independently from solvency shocks and applied in parallel to them, liquidity shocks are instead endogenously generated through mechanisms that model the liquidity-solvency nexus. The framework is applied to balance sheets of large financial institutions and provides interesting insights into the links between solvency and liquidity risk.
Chapter 3 proposes a network model for counterparty credit risk in the UK reinsurance market. A multi-layered network approach is used to incorporate information on reinsurance contract risk types and ownership structure for life and non-life insurers. The UK reinsurance sector is found to exhibit a 'small-world' property with a scale-free, core-periphery structure and topological characteristics common to other financial networks, making it 'robust-yet-fragile' to financial shocks. A stress simulation exercise shows the network to be robust to a shock to the value of total investments, and to idiosyncratic shocks to large, highly interconnected reinsurers.
Chapter 4 proposes a spatial epidemic model with demographic and geographic heterogeneity to study the regional dynamics of COVID-19 in England. The model provides a framework for assessing the impact of policies targeted towards sub-populations or regions. We define a concept of efficiency for comparative analysis of epidemic control policies and show targeted mitigation policies based on local monitoring to be more efficient than country-level or non-targeted measures.
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- Files:
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(Preview, Dissemination version, pdf, 18.3MB, Terms of use)
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Authors
Contributors
- Institution:
- University of Oxford
- Division:
- MPLS
- Department:
- Mathematical Institute
- Sub department:
- Mathematical Institute
- Oxford college:
- St Hugh's College
- Role:
- Supervisor
- Institution:
- University of Oxford
- Division:
- MPLS
- Department:
- Mathematical Institute
- Sub department:
- Mathematical Institute
- Role:
- Examiner
- Institution:
- University of Sussex
- Role:
- Examiner
- Funding agency for:
- Artur Kotlicki
- DOI:
- Type of award:
- DPhil
- Level of award:
- Doctoral
- Awarding institution:
- University of Oxford
- Language:
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English
- Keywords:
- Subjects:
- Deposit date:
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2021-11-21
- ARK identifier:
Terms of use
- Copyright holder:
- Kotlicki, A
- Copyright date:
- 2021
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