Financial Hazard Map: Financial Vulnerability Predicted by a Random Forests Classification Model
This study develops a systematic framework for assessing a country’s financial vulnerability using a predictive classification model of random forests. We introduce a new indicator that quantifies the potential loss in bank assets and measures a country’s overall vulnerability by aggregating these indicators across the banking sector. We also visualize the degree of vulnerability by creating a Financial Hazard Map that highlights countries and regions with underlying risks in their banking sectors.
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Financial Hazard Map: Financial Vulnerability Predicted by a Random Forests Classification Model
Semantic Scholar · Economics · 2018
Abstract
This study develops a systematic framework for assessing a country’s financial vulnerability using a predictive classification model of random forests. We introduce a new indicator that quantifies the potential loss in bank assets and measures a country’s overall vulnerability by aggregating these indicators across the banking sector. We also visualize the degree of vulnerability by creating a Financial Hazard Map that highlights countries and regions with underlying risks in their banking sectors.
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