Margin requirements and systemic liquidity risk

Bakoush, Mohamed; Gerding, Enrico H.; Wolfe, Simon

doi:10.1016/j.intfin.2018.09.007

Cited by 17 publications

(4 citation statements)

References 69 publications

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“…Similarly, Choon et al (2013) hold that GDP positively impacts liquidity risk. Conversely, Bakoush et al (2018) report an inverse association between liquidity risk and GDP while analyzing Malaysian Islamic banks.…”

Section: Literature Reviewmentioning

confidence: 96%

Liquidity risk and bank financial performance: an application of system GMM approach

Yahaya

Mahat

M.H.

et al. 2022

JFRC

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Purpose This study aims to examine the effect of liquidity risk on deposit money banks’ (DMBs) performance in Sub-Saharan Africa. This study also tests the interaction effect of liquidity risk and nonperforming loans on the performance of DMBs’ in Sub-Saharan Africa. Design/methodology/approach This study uses a two-step system generalized method of moment to test the influence of liquidity risk on DMBs’ performance in Sub-Saharan Africa. A sample of 50 listed banks across six Sub-Saharan African countries, including Nigeria, Ghana, South Africa, Zambia, Kenya and Tanzania, were used. The bank performance proxy used are return on asset and return on equity, while net interest margin is used for robustness check. Findings The study’s findings reveal a significant and negative association between liquidity risk and bank performance. Moreover, the relationship between the nonperforming loan and bank performance is negative and significant. Furthermore, the interaction effect of liquidity risk and nonperforming loans on bank performance is found to be significantly negative for the two proxies of bank performance. The result is robust for the alternative bank performance measurements and econometric model, which adequately addresses endogeneity tendency. Originality/value To the best of the researchers’ knowledge, this is one of the earliest empirical studies that examine the effect of liquidity risk on DMBs’ performance across Sub-Saharan African countries. This study further differs from previous studies with the interaction term of liquidity risk and nonperforming loan included in the model.

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Section: Literature Reviewmentioning

confidence: 96%

Liquidity risk and bank financial performance: an application of system GMM approach

Yahaya

Mahat

M.H.

et al. 2022

JFRC

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“…Since cash and available-for-sale securities are the most liquid assets on a bank's balance sheet, it is fairly normal for them to be volatile and to drive most of the Marginal Expected Shortfall. More recently, Bakoush et al (2019) or Nguyen et al (2020) also stress the importance of highly liquid instruments in avoiding systemic liquidity risk.…”

Section: Discussionmentioning

confidence: 99%

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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“…At the micro level, bank size [16,17], linkages among banks and other financial institutions [18][19][20], the size of shadow banking [21], and the financial condition of banks and other financial institutions [22,23] and other factors all have an impact on banking systemic risk. Systemic risk is also influenced at the macro level by variables like monetary policy [24], economic policy uncertainty [25], [26], and the procyclicality of the economy [27]. However, with the advent of the digital economy, data has become a new factor of production, leading to changes in the factors that constitute bank risk.…”

Section: Literature Reviewmentioning

confidence: 99%

Bank digital transformation, bank competitiveness and systemic risk

Jia,

Liu

2024

Front. Phys.

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The aim of this paper is to analyze the impact of the digital transformation of banks on their systemic risks. We find that the digital transformation of commercial banks can significantly inhibit the systemic risk of banks, and this conclusion is still valid after considering the endogeneity of the model. The bank’s digital transformation reduces its systemic risk by increasing its own competitiveness. Further analysis shows that the reduction of banks’ marginal costs due to digital transformation is a key factor in promoting banks’ competitiveness as the mechanism by which digital transformation reduces banks’ systemic risk. The role of bank digital transformation in reducing systemic risk is heterogeneous, which is more obvious in large commercial banks, commercial banks that have not established financial technology subsidiaries, and systemically important banks.

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Margin requirements and systemic liquidity risk

Cited by 17 publications

References 69 publications

Liquidity risk and bank financial performance: an application of system GMM approach

Liquidity risk and bank financial performance: an application of system GMM approach

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

Bank digital transformation, bank competitiveness and systemic risk

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