Basic Indicators of Systemic Risk in the EU Banking Sector. Implications for Banking Regulation

Sum, Katarzyna

doi:10.1515/ijme-2015-0027

Cited by 2 publications

(3 citation statements)

References 16 publications

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“…Our results give better insight into the link between balance-sheet liquidity proxies and systemic risk and call for the need for heightened prudential regulation of bank liquidity. This evidence-based assertion is also put forward by Tirole (2011) and Sum (2015). The findings yield some relevant implications for supervisory authorities.…”

Section: Discussionsupporting

confidence: 57%

“…Several authors investigate the nexus between bank balance-sheets and systemic risk: van den End and Tabbae (2012), Ahrend and Goujard (2015), Sum (2015), Hautsch et al (2015), Greenwood et al (2015), and Aldasoro and Faia (2016). Blau et al (2017) demonstrate that financial market efficiency is reduced by banks' "opacity", driven in part by the asset composition of their balance sheets.…”

Section: Literature Reviewmentioning

confidence: 99%

“…They compare liquidity and leverage variables in the wake of and after the crisis and conclude that balance-sheet data hint towards systemic vulnerabilities still. Sum (2015) considers balance-sheet indicators as straight-forward proxies of systemic risk when conducting an empirical analysis of the relationship between them and prudential regulation. Results indicate that further regulation is needed to target balance-sheet variables.…”

Section: Literature Reviewmentioning

confidence: 99%

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Modeling the Connection between Bank Systemic Risk and Balance-Sheet Liquidity Proxies through Random Forest Regressions

Zeldea

2020

Administrative Sciences

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Balance-sheet indicators may reflect, to a great extent, bank fragility. This inherent relationship is the object of theoretical models testing for balance-sheet vulnerabilities. In this sense, we aim to analyze whether systemic risk for a sample of US banks can be explained by a series of balance-sheet variables, considered as proxies for bank liquidity for the 2004:1–2019:1 period. We first compute Marginal Expected Shortfall values for the entities in our sample and then imbed them into a Random Forest regression setup. Although we discover that feature importance is rather bank-specific, we notice that cash and available-for-sale securities are the most relevant factors in explaining the dynamics of systemic risk. Our findings emphasize the need for heightened prudential regulation of bank liquidity, particularly in what concerns cash and immediate liquidity instrument weights. Moreover, systemic risk could be consistently tamed by consolidating bank emergency liquidity provision schemes.

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Section: Discussionsupporting

confidence: 57%

Section: Literature Reviewmentioning

confidence: 99%

Section: Literature Reviewmentioning

confidence: 99%

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Modeling the Connection between Bank Systemic Risk and Balance-Sheet Liquidity Proxies through Random Forest Regressions

Zeldea

2020

Administrative Sciences

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Systemic risk in the banking system: measuring and interpreting the results

Bezrodna

Ivanova

Onyshchenko

et al. 2019

Banks and Bank Systems

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Highly concentrated banking system risks and the cumulative effect due to their accumulation act as a driver for improving the macro-prudential policy implemented by central banks. For this reason, an effectively and comprehensively assessed systemic risk in the banking system is declared an express condition for the early detection of its production sources and blocking of potential spreading channels, reducing the possible implementation. In light of this, the article develops an approach to the aggregated systemic risk assessment and interpretation of its results. The proposed approach is based on the considered influence exerted by financial risks of systemically important banks on the destabilized banking system and interconnections between banks in the context of the possible crisis impulse spreading. The following steps should be accomplished to form an aggregated systemic risk indicator in the banking system. Firstly, the differentiation of systemically important banks by the degree of their systemic importance; secondly, an integral assessment of the bank operation riskiness within certain bank groups; thirdly, the cumulative composition of the corresponding integral indicators, taking into account their weighting coefficients based on two criteria, namely values of the systemic importance indicator differentiating the bank groups, and the correlation of their risks. Interpreting the quantitative measurement results with regard to the systemic risk in the banking system is followed by the recommendations below: the systemic risk grading into high, medium and low levels and the respective definition of the threshold aggregated systemic risk indicator value which informs about the possible systemic crisis when approached; justification of the selected supervision regime types (strengthened, moderate or weakened) for systemically important banks, depending on the riskiness level specific for their operation and the systemic importance degree. The developed approach to measuring the systemic risk by means of constructing an aggregated indicator and interpreting the obtained results was being tested considering the financial risk indicators of the systemically important banks in Ukraine during 2009–2018.

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Basic Indicators of Systemic Risk in the EU Banking Sector. Implications for Banking Regulation

Cited by 2 publications

References 16 publications

Modeling the Connection between Bank Systemic Risk and Balance-Sheet Liquidity Proxies through Random Forest Regressions

Modeling the Connection between Bank Systemic Risk and Balance-Sheet Liquidity Proxies through Random Forest Regressions

Systemic risk in the banking system: measuring and interpreting the results

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