Modeling the Connection between Bank Systemic Risk and Balance-Sheet Liquidity Proxies through Random Forest Regressions
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-s...
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| Format: | Article |
| Language: | English |
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MDPI AG
2020-08-01
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| Series: | Administrative Sciences |
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| Online Access: | https://www.mdpi.com/2076-3387/10/3/52 |
| _version_ | 1797559434656874496 |
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| author | Cristina Zeldea |
| author_facet | Cristina Zeldea |
| author_sort | Cristina Zeldea |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-03-10T17:45:24Z |
| format | Article |
| id | doaj.art-e0f2b0fa60d242ef8dc7e588f57622d6 |
| institution | Directory Open Access Journal |
| issn | 2076-3387 |
| language | English |
| last_indexed | 2024-03-10T17:45:24Z |
| publishDate | 2020-08-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Administrative Sciences |
| spelling | doaj.art-e0f2b0fa60d242ef8dc7e588f57622d62023-11-20T09:33:40ZengMDPI AGAdministrative Sciences2076-33872020-08-011035210.3390/admsci10030052Modeling the Connection between Bank Systemic Risk and Balance-Sheet Liquidity Proxies through Random Forest RegressionsCristina Zeldea0Doctoral School of International Business and Economics, Bucharest University of Economic Studies, 010374 Bucharest, RomaniaBalance-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.https://www.mdpi.com/2076-3387/10/3/52systemic riskMarginal Expected ShortfallRandom Forest regressionbalance-sheet data |
| spellingShingle | Cristina Zeldea Modeling the Connection between Bank Systemic Risk and Balance-Sheet Liquidity Proxies through Random Forest Regressions Administrative Sciences systemic risk Marginal Expected Shortfall Random Forest regression balance-sheet data |
| title | Modeling the Connection between Bank Systemic Risk and Balance-Sheet Liquidity Proxies through Random Forest Regressions |
| title_full | Modeling the Connection between Bank Systemic Risk and Balance-Sheet Liquidity Proxies through Random Forest Regressions |
| title_fullStr | Modeling the Connection between Bank Systemic Risk and Balance-Sheet Liquidity Proxies through Random Forest Regressions |
| title_full_unstemmed | Modeling the Connection between Bank Systemic Risk and Balance-Sheet Liquidity Proxies through Random Forest Regressions |
| title_short | Modeling the Connection between Bank Systemic Risk and Balance-Sheet Liquidity Proxies through Random Forest Regressions |
| title_sort | modeling the connection between bank systemic risk and balance sheet liquidity proxies through random forest regressions |
| topic | systemic risk Marginal Expected Shortfall Random Forest regression balance-sheet data |
| url | https://www.mdpi.com/2076-3387/10/3/52 |
| work_keys_str_mv | AT cristinazeldea modelingtheconnectionbetweenbanksystemicriskandbalancesheetliquidityproxiesthroughrandomforestregressions |