Agent-Based Simulation of Central Bank Digital Currencies
Abstract: This paper presents a multi-period agent-based model for the study of macro-financial effects related to the introduction of a retail Central Bank Digital Currency (CBDC). Calibrating it with aggregate statistics of the German retail payment market, we exemplify how the model can be used to quantify the impact of a CBDC on i) the usage of alternative means of payments, ii) the composition of consumer's wealth, and iii) the banking sector disintermediation. We find that CBDC can be configured without largely impacting the banking sector balance sheet. However, we also find that card companies may suffer a substantial decline in their transaction revenues. We see this model as a framework that can be enriched and tuned to answer a myriad of questions relevant to different jurisdictions from a macro-financial angle. The model is publicly available in the FNA simulation platform for running other policy experiments i.e., testing the efficacy of alternative configurations of CBDCs.
Network Sensitivity of Systemic Risk
Abstract: A growing body of studies on systemic risk in financial markets has emphasized the key importance of taking into consideration the complex interconnections among financial institutions. Much effort has been put into modeling the contagion dynamics of financial shocks, and assessing the resilience of specific financial markets—either using real network data, reconstruction techniques, or simple toy networks. Here we address the more general problem of how shock propagation dynamics depend on the topological details of the underlying network. To this end, we consider different realistic network topologies, all consistent with balance sheets information obtained from real data on financial institutions. In particular, we consider networks of varying density and with different block structures, and diversify as well in the details of the shock propagation dynamics. We confirm that the systemic risk properties of a financial network are extremely sensitive to its network features. Our results can aid in the design of regulatory policies to improve the robustness of financial markets.
Backtesting Macroprudential Stress Test
Abstract: Macroprudential stress tests generate a wide range of stress outcomes, depending on the chosen input parameters. Building on the concept of reverse stress tests, we embrace this parameter sensitivity in a backtesting exercise. We consider models of price-mediated contagion among banks, which interpolate between different liquidation dynamics. We then test the capability of these models to predict actual bank non-/defaults in the United States for the years 2008-10. While the model performance depends on the type of shock being imposed, we find that the model often performs better than alternative benchmarks that do not account for common asset holdings. We also show how the results depend on the initial shock level, the market impact parameter, the number of asset liquidation rounds, and the chosen liquidation functions.
Modelling Fire Sale Contagion across Banks and Non-Banks
Abstract: We study the impact of common asset holdings across different financial sectors on financial stability. In particular, we model indirect contagion via fire sales across UK banks and non-banks. Fire sales are triggered by different responses to a financial shock: banks and non unit-linked insurers are subject to regulatory constraints, while funds and unit-linked insurers are obliged to meet investor redemptions. We use our model to conduct a systemic stress simulation under different initial shock scenarios and institutions’ selling strategies. We find that performing a stress simulation that does not account for common asset holdings across multiple sectors can severely underestimate the fire sale losses in the financial system. We also show that a pro-rata liquidation strategy would result in a higher level of fire sale losses, but a waterfall strategy may produce a higher spillover effect for a passive institution (or a passive sector) that chooses not to liquidate any of its assets during distress.