The financial crisis of 2007-2008 was a severe global crisis causing a worldwide recession. One of the main contributing factors of the crisis was the excessive risk appetite of banks and financial institutions. Since then, regulatory authorities and financial institutions have directed focus towards risk management with the main objective to avert a similar crisis from occurring in the future. The aim of this thesis is to investigate how an adverse macroeconomic scenario would affect the migrations between risk classes of an SME portfolio, referred to as stress test. This thesis utilises two frameworks, one by Belkin and Suchower and one by Carlehed and Petrov, for creating a single systematic indicator describing the credit class migrations of the portfolio. Four different regression model setups (Ordinary Least Squares, Additive Model, XGBoost and SVM) are then used to describe the relationship between macroeconomic indicators and this systematic indicator. The four models are evaluated in terms of interpretability and ability to predict in order to find the main drivers for the systematic indicator. Their corresponding prediction errors are compared to find the best model. The portfolio is stress tested by using the regression models to predict the corresponding systematic indicator given an adverse macroeconomic scenario. The probability of default, estimated from the indicator using each of the frameworks, are then compared and analysed with regards to the systematic indicator. The results show that unemployment is the main driver of the risk class migrations for an SME portfolio, both from a statistical and economical perspective. The most appropriate regression model is the additive model because of its performance and interpretability and is therefore advised to use for this problem. From the PD estimations, it is concluded that the framework by Belkin and Suchower gives a more volatile estimate than that of Carlehed and Petrov.
| Identifer | oai:union.ndltd.org:UPSALLA1/oai:DiVA.org:umu-185398 |
| Date | January 2021 |
| Creators | Almqvist, Siri, Nordin, Oskar |
| Publisher | Umeå universitet, Institutionen för matematik och matematisk statistik |
| 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 |
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