Description
Aims:
Overall, the module represents an introduction to the topic of systemic risk and stress propagation in networked systems. The first part of the module presents a general introduction to complex networks and dynamical processes; the second part is focused on specific applications to the study of contagion in financial networks.
Intended learning outcomes:
On successful completion of the module, a student will be able to:
- Compute network metrics and provide a statistical description of networks.
- Analyse dynamical processes on networks.
- Implement simple algorithms for the analysis of financial contagion.
Indicative content:
The following are indicative of the topics the module will typically cover:
Introduction to complex networks:
- Basic concepts of networks (graphs, subgraphs, adjacency matrix, undirected, directed and weighted networks), common metrics (degree, centrality, clustering, degree distribution, excess degree distribution, mixing patterns, real world examples).
- Network models (random networks, configuration model, small world, preferential attachment).
- Maximum-entropy networks.
Collective behaviour:
- Emergence of a giant cluster. Robustness to random and targeted attacks.
- Epidemic spreading processes on networks.
- Cascade processes on networks.
Application to interbank networks and systemic risk:
- Interbank networks and their properties.
- Modelling contagion due to counterparty default risk.
- Modelling contagion due to overlapping portfolios and fire sales.
- Identifying systemically important institutions.
- Reverse stress testing.
- Leverage cycles.
Requisites:
To be eligible to select this module as optional or elective, a student must: (1) be registered on a programme and year of study for which it is a formally available; and (2) have familiarity with basic probability and calculus. The assessment will require basic programming skills.
Module deliveries for 2024/25 academic year
Last updated
This module description was last updated on 19th August 2024.
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