Financial Hazard Map: Financial Vulnerability Predicted by a Random Forests Classification Model

• Tanaka, Katsuyuki

• Kinkyo, Takuji

• Hamori, Shigeyuki

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.

Journal

• Sustainability

  Sustainability 10 (5), 1530-1530, 2018-05-11

  MDPI

Keywords

• financial hazard map
• random forests
• early warning system
• bank failure

Details

• CRID: 1050012570393440128
• NII Article ID: 120006488453
• DOI: 10.3390/su10051530
• ISSN: 20711050
• HANDLE: 20.500.14094/90005004
• Web Site: http://www.mdpi.com/2071-1050/10/5/1530/pdf
• Text Lang: en
• Article Type: journal article
• Data Source:
  • IRDB
  • Crossref
  • CiNii Articles
  • KAKEN