Financial Hazard Map: Financial Vulnerability Predicted by a Random Forests Classification Model
Katsuyuki Tanaka,
Takuji Kinkyo and
Shigeyuki Hamori
Additional contact information
Takuji Kinkyo: Graduate School of Economics, Kobe University, 2-1, Rokkodai, Nada-Ku, Kobe 657-8501, Japan
Sustainability, 2018, vol. 10, issue 5, 1-18
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.
Keywords: financial hazard map; random forests; early warning system; bank failure (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2018
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (6)
Downloads: (external link)
https://www.mdpi.com/2071-1050/10/5/1530/pdf (application/pdf)
https://www.mdpi.com/2071-1050/10/5/1530/ (text/html)
Related works:
Working Paper: Financial Hazard Map: Financial Vulnerability Predicted by a Random Forests Classification Model (2017)
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:gam:jsusta:v:10:y:2018:i:5:p:1530-:d:145799
Access Statistics for this article
Sustainability is currently edited by Ms. Alexandra Wu
More articles in Sustainability from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().