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Credit Scoring Models Based on Monitoring the Behaviour of Debtors
Škovroňová, Lenka ; Marosi, Gabriel (advisor) ; Hurt, Jan (referee)
Text of this thesis is divided into five main parts. In opening part we put mind to credit risk and credit process, describing various bank clients. There are trends in loans development by client sectors underlined. In second part there is a survey of mathematical models which are widely used in real life for client creditworthiness analysis. In next part you can find a detailed description of theory for logistic regression model and for new developed random walk model resulting from commercial KMV model. Suitting of random walk model to predicting default of retail clients on their overdrafts is mentioned. The fourth part begins with description of data used. Then the numeric work for both mentioned models is focused, using results of logistic regression model as performance measure of new random walk model. The conclusion pays to draw out some possible future improvements of new model.
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Credit Scoring Models Based on Monitoring the Behaviour of Debtors
Škovroňová, Lenka ; Hurt, Jan (referee) ; Marosi, Gabriel (advisor)
Text of this thesis is divided into five main parts. In opening part we put mind to credit risk and credit process, describing various bank clients. There are trends in loans development by client sectors underlined. In second part there is a survey of mathematical models which are widely used in real life for client creditworthiness analysis. In next part you can find a detailed description of theory for logistic regression model and for new developed random walk model resulting from commercial KMV model. Suitting of random walk model to predicting default of retail clients on their overdrafts is mentioned. The fourth part begins with description of data used. Then the numeric work for both mentioned models is focused, using results of logistic regression model as performance measure of new random walk model. The conclusion pays to draw out some possible future improvements of new model.
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Credit Scoring Models
Drahá, Ivana ; Hurt, Jan (referee) ; Marosi, Gabriel (advisor)
Diploma t hesis deals with fund ament al attributes of credit risks, hist orie development of models and selected statist ical methods for counter party risk meas urement . The mat erial is focused on aplication of cluster analysis and logisti c regression. Fur ther , it provides overview of meas ur ing the effectivity of models, The final par t present s dat a processing in t he SAS software package, findin gs on influence of categorical data repr esentation to model efficiency and depend ence of model efficicncy on size of underlying development sample.
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Modeling Risk of a Credit Portfolio
Němeček, Tomáš ; Marosi, Gabriel (advisor) ; Hurt, Jan (referee)
Úvěrové riziko je ve finančním sektoru stále největším zdrojem rizika a jeho špatné měření a řízení může vést k obrovským ztrátám. Tato diplomová práce se zabývá metodami modelování (měření) velikosti úvěrového rizika na portfoliové bázi. První část se zabývá regulatorním přístupem k měření úvěrového rizika, který vychází z posledních regulatorních opatření známých pod názvem Basel II. Věnuje se zejména pokročilejšímu IRB (Internal Rating Based) přístupu. Druhá část je věnována modelu CreditMetrics společnosti J.P. Morgan. Výsledky obou přístupů jsou demonstrovány na korporátním úvěrovém portfoliu jedné z největších českých bank (České spořitelny, a.s.). Veškerá potřebná data, výpočty a výsledky jsou uložena na přiloženém CD.
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