Quantifying Systemic Risk in the Presence of Unlisted Banks: Application to the European Banking Sector
Published: 06 March 2023
We propose a credit portfolio approach for evaluating systemic risk and attributing it across institutions. We construct a model that can be estimated from high-frequency CDS data. This captures risks from publicly traded banks, privately held institutions, and cooperative banks, extending approaches that rely on information from the public equity market only. We account for correlated losses between the institutions, overcoming a modeling weakness in earlier studies. We also offer a modeling extension to account for fat tails and skewness of asset returns. The model is applied to a universe of banks where we find discrepancies between the capital adequacy of the largest contributors to systemic risk relative to less systemically important banks on a European scale.
Keywords: systemic risk; CDS rates; implied market measures; financial institutions; fat tails; O-SII buffers
JEL codes G01; G20; G18; G38
Working paper no. 768
Quantifying Systemic Risk in the Presence of Unlisted Banks: Application to the European Banking Sector
Research Highlights:
- This paper proposes a model for measuring systemic risk over time and attributing it across financial institutions.
- The model is following a credit risk approach and is calibrated on high-frequency CDS data, allowing the study of banks which are not publicly traded on the equity market.
- We extend the existing literature on systemic risk measurement by allowing for correlated losses between the institutions, accounting for fat tails and skewness of asset returns.
- Applying the model on a European scale, we find discrepancies between the capital adequacy of the largest contributors to systemic risk relative to less systemically important banks, engaging in the debate on macroprudential capital regulation in Europe.
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