A framework for simulating systemic risk and its application to the South African banking sector

Abstract

We present a network-based framework for simulating systemic risk that considers shock propagation in banking systems. In particular, the framework allows the modeller to reflect a topdown framework where a shock to one bank in the system affects the solvency and liquidity position of other banks, through systemic market risks and consequential liquidity strains. We illustrate the framework with an application using South African bank balance sheet data. Spikes in simulated assessments of systemic risk agree closely with spikes in documented subjective assessments of this risk. This indicates that network models can be useful for monitoring systemic risk levels. The model results are sensitive to liquidity risk and market sentiment and therefore the related parameters are important considerations when using a network approach to systemic risk modelling.

A computable general equilibrium model for banking sector risk assessment in South Africa

“…The data is publicly available as standardized monthly balance sheet data (BA900) that are provided by individual South African banks. The extraction of the data is described in Walters et al (2018) which made use of the monthly data from April 2015 to March 2017. The assets were grouped into short term, medium term, long term and interbank lending.…”

Systemic risk enacted by emotionally driven client behaviour on South African mobile banking systems: A structured literature review through the theoretical lens of interpersonal behaviour

“…Systemic risk can be defined as the risk that an unexpected event, known as a systemic event, could result in considerable loss and damage to the financial market, including the banking system (Ellis et al, 2021). A systemic event is typically caused by either an internal or external shock to the financial market (F. J. C. Beyers et al, 2018;Guerra et al, 2016). Main sources of systemic risk for banks, which could cause such a systemic event, are bank size and interconnectedness.…”

“…A large bank would cause a much bigger loss to the financial market in the event of a default than a smaller bank (Bostandzic & Weiß, 2018;Klaassen, 2020). The bigger the bank, the more interconnected or linked (via interbank loans) it is likely to be with other banks (Badarau & Lapteacru, 2020;F. J. C. Beyers et al, 2018;Bostandzic & Weiß, 2018).…”