One of banks core businesses today is to, in various ways, lend capital to the market and in return receive interest rate. But giving out credit comes with great risk and, therefore, precautions need to be taken. It is impossible to forecast exactly which obligor (borrower) that will default on its exposure. However, with well functioning risk management, institutions can lower the severity of their loss. In this study, we consider using a multi-factor model to calculate concentration risk for Swedish credit portfolios, which is a type of credit risk that is usually caused by high concentration of credit exposures distributed over few industrial sectors. In its existing form, the multi-factor model uses fixed sector correlations with predetermined sectors as input. Instead, we propose to use a data-driven approach based on data from the Stockholm stock exchange. In a simulation study, we find that the distributions of total credit loss are somewhat different under the original approach than under our proposed approach. This suggests that further research is needed to investigate whether the two approaches are interchangeable.
| Identifer | oai:union.ndltd.org:UPSALLA1/oai:DiVA.org:uu-486560 |
| Date | January 2022 |
| Creators | Norrbin, Victor |
| Publisher | Uppsala universitet, Statistiska institutionen |
| Source Sets | DiVA Archive at Upsalla University |
| Language | English |
| Detected Language | English |
| Type | Student thesis, info:eu-repo/semantics/bachelorThesis, text |
| Format | application/pdf |
| Rights | info:eu-repo/semantics/openAccess |
Page generated in 0.002 seconds