Measuring capital at risk in the UK banking sector

Giovanni Covi, James Brookes and Charumathi Raja

How banks are exposed to the financial system and real-economy determines concentration risk and interconnectedness in the banking sector, and in turn, the severity of tail-events. We construct the Global Network data set, a comprehensive exposure-based data set of the UK banking sector, updated quarterly, covering roughly 90% of total assets. We use it to study the UK banking system’s microstructure and estimate the likelihood and severity of tail-events. We find that during the Covid-19 (Covid) pandemic, the likelihood and severity of tail-events in the UK banking sector increased. The probability of an extreme stress event with losses above £91 billion (roughly 19% of CET1 capital) increased from 1% before the pandemic to 4.1% in 2020 Q2, subsequently falling to 1.7% in 2021 Q4.

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On the origin of systemic risk

Giovanni Covi, Mattia Montagna and Gabriele Torri

Systemic risk in the bank sector is often associated with long periods of economic downturn and large social costs. In a new paper, we develop a microstructural contagion model to disentangle and quantify the different sources of systemic risk for the euro-area banking system. Calibrated to granular euro-area data, we estimate that the probability of a systemic banking crisis was around 3.6% in 2018. Seventy per cent of the risk stems from economic risks, with fire sales and contagion risk accounting for most of the remainder and only a small role for interbank exposures. Our findings suggest that correlations among banks’ losses play a crucial role in the origins of systemic risk.

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Playing with fire: banks’ distressed sales under solvency and liquidity constraints

Caterina Lepore and Jamie Coen

Many commentators on the global financial crisis identified ‘fire sales’ as one of the key mechanisms by which shocks to banks were amplified and transmitted across the wider financial system. When firms in distress sell assets held by other institutions at discounted prices, losses can spread through the financial system as prices fall, amplifying the initial stress. In a working paper published last year, we explored this mechanism by presenting a new model of fire sales. In doing so, we answer the following questions: Which types of financial shocks combine to produce fire sales? How can banks optimally liquidate their portfolios when forced to do so? How big a risk are bank fire sales?

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The decline of solvency contagion risk

Marco Bardoscia, Paolo Barucca, Adam Brinley Codd and John Hill

The failure of Lehman Brothers on 15 September 2008 sent shockwaves around the world. But the losses at Lehman Brothers were only the start of the problem. The price of their bonds halved, almost overnight. Other institutions that held Lehman’s debt faced huge losses, and markets feared that those losses could trigger further failures. The good news is that our latest research suggests that risks within the UK banking system from one such contagion channel, “solvency contagion”, have declined sharply since 2008. We have developed a new model which quantifies risk from this channel, and helps us understand why it has fallen. Regulators are using the model to monitor this particular source of risk as part of the Bank’s annual concurrent stress test exercise.

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The “question” or the “answer”? Market reaction to UK stress tests

Matthieu Chavaz, Jeremy Chiu and Evarist Stoja.

How might banks fare in stressful macroeconomic conditions? Are they strong enough to withstand the stress and survive or will they fall like dominoes? Stress tests offer insights into such questions.

Regulators are not only making a growing usage of such tests, they are also increasingly inclined to communicate openly about them. This is a remarkable evolution. Throughout history, regulators have typically followed some form of Hippocratic Oath and refrained from disclosing their detailed diagnostics of individual banks’ health. Regulators are now increasingly keen to release both the “answer” to stress tests (the results) and the “question” – the stress scenario regulators confront banks with. This column suggests that the disclosure of the scenario can be as important as – if not more than – the disclosure of the results.

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Bringing together stress testing and capital models – a Bayesian approach

Dan Georgescu & Manuel Sales.

Capital requirements for financial institutions are typically calculated using a statistical model and a risk measure such as VaR, whereas stress tests designed by regulators and risk managers are often based on subjective scenarios with no associated probability level. The stress test cannot therefore be easily linked to the capital measure. Taking insurance as an example, we show how to establish the link using intuitive tools which (i) respect the stress test designer’s intuition about causal direction, (ii) can be calibrated to pre-determined parameters such as correlations between risks, and (iii) can be easily communicated to and challenged by non-technical audiences.

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