The banking industry, during its operations, faces various risks which, if mismanaged, can lead to a situation of financial distress, or in the worst case scenario to bankruptcy. Due to the interconnectedness of the banking system, a stressful situation of one bank can be transmitted to the others and lead to a situation of financial instability in the system. To avoid such situations, governments and supervisors have several tools. To monitor financial institutions, regulators can conduct off-site examinations based on published balance sheet data. In doing so, however, regulators can take information from market participants to better monitor. Indeed, the resources, knowledge and incentives of the private sector to monitor financial institutions may lead them to collect information more frequently and more accurately. So the main purpose of the thesis is to verify if adding market-based indicators (beyond accounting based and macroeconomic based indicators) in an Early Warning System to predict banking distress improves the accuracy of the model.
The banking industry, during its operations, faces various risks which, if mismanaged, can lead to a situation of financial distress, or in the worst case scenario to bankruptcy. Due to the interconnectedness of the banking system, a stressful situation of one bank can be transmitted to the others and lead to a situation of financial instability in the system. To avoid such situations, governments and supervisors have several tools. To monitor financial institutions, regulators can conduct off-site examinations based on published balance sheet data. In doing so, however, regulators can take information from market participants to better monitor. Indeed, the resources, knowledge and incentives of the private sector to monitor financial institutions may lead them to collect information more frequently and more accurately. So the main purpose of the thesis is to verify if adding market-based indicators (beyond accounting based and macroeconomic based indicators) in an Early Warning System to predict banking distress improves the accuracy of the model.
Market information as indicators of bank financial distress
COCCI, ALAIN
2022/2023
Abstract
The banking industry, during its operations, faces various risks which, if mismanaged, can lead to a situation of financial distress, or in the worst case scenario to bankruptcy. Due to the interconnectedness of the banking system, a stressful situation of one bank can be transmitted to the others and lead to a situation of financial instability in the system. To avoid such situations, governments and supervisors have several tools. To monitor financial institutions, regulators can conduct off-site examinations based on published balance sheet data. In doing so, however, regulators can take information from market participants to better monitor. Indeed, the resources, knowledge and incentives of the private sector to monitor financial institutions may lead them to collect information more frequently and more accurately. So the main purpose of the thesis is to verify if adding market-based indicators (beyond accounting based and macroeconomic based indicators) in an Early Warning System to predict banking distress improves the accuracy of the model.File | Dimensione | Formato | |
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https://hdl.handle.net/20.500.12608/48234