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Contribution Details
| Type | Master's Thesis |
| Scope | Discipline-based scholarship |
| Title | Bankruptcy Prediction for European Companies |
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| Institution | University of Zurich |
| Faculty | Faculty of Business, Economics and Informatics |
| Number of Pages | 78 |
| Date | 2022 |
| Abstract Text | The effect of firms’ financial characteristics and macroeconomic conditions were examined. Furthermore, the influence of dynamic variables on classification performance was investigated. Data on firms from eight different European countries were collected and analyzed. Six different statistical models were employed and optimally tuned, and they revealed that prediction performance is significantly increased if macroeconomic conditions are included. The dynamic component was shown to enhance model prediction for most classification methods. Classification models were compared with each other, and significant differences in classification power were observed. Overall, the results imply a significant improvement if macroeconomic conditions and dynamic variables are included. |
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