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The Estimation of Probability of Default Using Logistic Regression
 Jiřičko, Pavel ; Dlouhá, Zuzana (advisor) ; Formánek, Tomáš (referee)
The aim of the thesis was to build a probability prediction model for client loan repayment. First, the author selected suitable explanatory variables and explained these in detail in the thesis. The author examined various quantities both for qualitative variables (e.g. failure rates and scores) and quantitative variables (e.g. means and standard deviations) describing individual categories. The predictions were done by the use of logistic regression. The estimated coefficients of individual explanatory variables were examined in terms of their statistical significance. The author also described the impact of individual explanatory variables on the probability of a clients default. The probabilities were calculated for two clients with specific values of explanatory variables. The author managed to build a model that can be used to predict probability of client loan repayment defaults.
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