Describing financial crisis propagation through epidemic modelling on multiplex networks

Bozhidarova, Malvina; Ball, Frank; van Gennip, Yves; O'Dea, Reuben D.; Stupfler, Gilles

Abstract

This paper proposes a novel framework for modelling the spread of financial crises in complex networks, combining financial data, Extreme Value Theory and an epidemiological transmission model. We accommodate two key aspects of contagion modelling: fundamentals-based contagion, where the transmission is due to direct financial linkages, and pure contagion, where a crisis might trigger additional crises due to global effects. We use stock price, geographical location and economic sector data for a set of 398 companies to construct multiplex networks of four layers, on which a susceptible-infected-recovered transmission model is defined, in order to model the spread of financial shocks between companies by accounting for their interconnected nature. By utilizing stock price data for the 2008 and 2020 financial crises, we investigate and assess the effectiveness of our model in forecasting the propagation of financial shocks through the network, where a shock is detected by measuring stock price volatility. The results suggest that the proposed framework is effective in predicting the spread of financial crises. Our findings demonstrate the significance of each layer of the multiplex network structure, which differentiates between various transmission pathways, for predicting the number of affected companies, as well as for company-, sector- or location-specific predictions.

• Journal Article Type: Article
• Acceptance Date: Feb 29, 2024
• Online Publication Date: Apr 10, 2024
• Publication Date: 2024-04
• Deposit Date: Mar 28, 2024
• Publicly Available Date: Apr 11, 2024
• Journal: Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences
• Print ISSN: 1364-5021
• Electronic ISSN: 1471-2946
• Publisher: The Royal Society
• Peer Reviewed: Peer Reviewed
• Volume: 480
• Issue: 2287
• Article Number: 20230787
• DOI: https://doi.org/10.1098/rspa.2023.0787
• Keywords: Applied mathematics; mathematical modelling; mathematical finance; Epidemic modelling; Financial crisis; Multiplex network; SIR model; Tail dependence
• Public URL: https://nottingham-repository.worktribe.com/output/33023537
• Publisher URL: https://royalsocietypublishing.org/doi/10.1098/rspa.2023.0787
• Additional Information: Received: 2023-10-23; Accepted: 2024-02-29; Published: 2024-04-10