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Rating Model for the Internal Assessment of the Creditworthiness of Customers
Vaňková, Leona ; Kotěrová, Monika (referee) ; Kocmanová, Alena (advisor)
The object of the following Diploma thesis was to design and test a simple and well-arranged credit tool – a Rating Model (further Model) which could be used as a preventative measure in credit policy. This rating model was designed in order to make the work of the Credit Risk Management sub-department and Rating Committee of KORADO more effective and at the same time to make more effective use of currently available internal and external data. Should the Company decide to use this Rating Model, a minimum of additional expenses would be incurred. The reader of this work will gain theoretical knowledge regarding financial analysis, credit management and fuzzy logic which is used in the calculation of a Total Rating. He/she will become acquainted with the major external agencies providing rating evaluations. As well, the reader may apprise the theoretical Rating model, including its practical use on four domestic and four overseas customers of KORADO. In conclusion there is an implementation of the Model, including a time schedule, an implementation team proposal as well as a budget of implementation and utilization costs.
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Binning numerical variables in credit risk models
Mattanelli, Matyáš ; Baruník, Jozef (advisor) ; Teplý, Petr (referee)
This thesis investigates the effect of binning numerical variables on the per- formance of credit risk models. The differences are evaluated utilizing five publicly available data sets, six evaluation metrics, and a rigorous statistical test. The results suggest that the binning transformation has a positive and significant effect on the performance of logistic regression, feedforward artifi- cial neural network, and the Naïve Bayes classifier. The most affected aspect of model performance appears to be its ability to differentiate between eligible and ineligible customers. The obtained evidence is particularly pronounced for moderately-sized data sets. In addition, the findings are robust to the inclusion of missing values, the elimination of outliers, and the exclusion of categorical features. No significant positive effect of the binning transformation was found for the decision tree algorithm and the Random Forest model.
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Receivables Management and Credit Risk in a Selected Company
PETŘÍKOVÁ, Markéta
The master's thesis is focused on the issue of receivables management and credit risk. The aim is to describe and evaluate the selected company's business strategy to receivables and credit risk management. Furthermore, the aim is to propose measures to improve this strategy of the company. The thesis is divided into a theoretical and a practical part. The analysis of the company is focused on the company's strategy in providing business loans, evaluating and monitoring the purchasers, setting their business conditions and solving problem debts. In this thesis, the current strategy of the company is evaluated, and new measures are proposed. The recommended improvements will increase the number of customers and the competitive ability of the analysed company. In the main part of the thesis, it is proposed to group together the customers of the company that share the same or similar characteristics using a cluster analysis. The implementation of such analysis can help the company to better identify its customers and consequently to provide their customers with more suitable business and credit conditions. Furthermore, a system for debt collection is proposed and an investment in a supplementary instrument to the existing accounting system is recommended. The cost of the investment is compared with the cost of the time spent generating and sending reminders. The recommended improvements will increase the number of customers and the competitive ability of the analysed company.
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Models of default prediction of a client
Hezoučká, Šárka ; Černý, Rostislav (advisor) ; Hurt, Jan (referee)
The aim of the presented work is to investigate possible improvement of scor- ing models prediction power in retail credit segment by using structural models estimating the future development of behavioral score. These models contain the information about past development of the behavioral score by parameters which take into account the sensitivity of clients' probability of default on in- dividual market and life changes. These parameters are estimated with Markov Chain Monte Carlo methods based on score history. Eight different types of struc- tural models were applied on the real data. The diversification measure of indivi- dual models is compared using the Gini coefficient. These structural models were compared with each other and also with the existing scoring model of the credit institution which provided the underlying data. 1
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Credit Default Swap
Kratochvíl, Matěj ; Chudoba, Martin (advisor) ; Hurt, Jan (referee)
of the Bachelor Thesis Title: Credit Default Swap Author: Matěj Kratochvíl Department: Department of Probability and Mathematical Statistics Supervisor: Mgr. et Mgr. Martin Chudoba Abstract: The thesis deals with basic credit derivative - credit default swap. The aim of the first part is to explain its mechanism, contract elements, settlement, and to show practical examples of investment. The second part attempts to clarify how the arbitrage possibilities between bond market and credit derivatives market drive credit default swap prices to a certain range. Further there is presented a simple pricing model and possibilities of its exploitation. Examples are provided for better understanding. The third part focuses on counterparty default risk in credit default swap. Keywords: CDS, default intensity, credit risk
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Credit risk
Srbová, Eliška ; Herman, Jiří (advisor) ; Hurt, Jan (referee)
This thesis deals with credit risk and selected methods of its evalua- tion. It is focused on assumptions, calculation methods, results and specifics of the CreditMetrics and the CreditRisk+ models. The CreditRisk+ model analytically determines the portfolio credit losses distribution that is caused by defaults of counterparties. In the CreditMetrics model, the credit migration risk is addition- ally considered and the future portfolio value distribution is calculated using the Monte Carlo simulation. The third approach covered in this thesis is the Solvency II, the set of requirements proposed by the European Union for determination of regulatory capital for insurance companies. In the practical part the three ap- proaches are applied on a set of three portfolios of different credit quality. Their results, particularly the determined level of capital required to cover the risk of unexpected credit losses, are analyzed and compared.
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Markov chains and credit risk theory
Cvrčková, Květa ; Prokešová, Michaela (advisor) ; Lachout, Petr (referee)
Markov chains have been widely used to the credit risk measurement in the last years. Using these chains we can model movements and distribution of clients within rating grades. However, various types of markov chains could be used. The goal of the theses is to present these types together with their advan- tages and disadvantages. We focus our attention primarily on various parameter estimation methods and hypotheses testing about the parameters. The theses should help the reader with a decision, which model of a markov chain and which method of estimation should be used for him observed data. We focus our attention primarily on the following models: a discrete-time markov chain, a continuous-time markov chain (we estimate based on continuous- time observations even discrete-time observations), moreover we present an even- tuality of using semi-markov chains and semiparametric multiplicative hazard model applied on transition intensities. We illustrate the presented methods on simulation experiments and simu- lation studies in the concluding part. Keywords: credit risk, markov chain, estimates in markov chains, probability of default 1
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An Empirical Analysis of Liquidity Situation and Interbank Rates in the Czech Republic during Global Crisis
Lešanovská, Jitka ; Geršl, Adam (advisor) ; von Terzi, Martina (referee)
This diploma thesis focuses on the development of the interbank market liquidity and interest rates in the Czech interbank market with special focus on the period of global crisis. We analyze determinants of the interbank interest rates and their development with respect to the key monetary policy rate. We explain the significant departure of the interbank interest rates from the key monetary policy rate (impairment of monetary policy transmission) during the global crisis by an increase in risk premia on interbank lending. The source of the risk premia is decomposed into the individual components such as liquidity risk, counterparty risk, foreign influence and other factors. Their contribution to the overall risk premia over time during the global crisis is analyzed. We find that the liquidity risk was the key determinant of tensions in the Czech interbank market in the beginning of the global crisis. However, its influence weakened over time while the role of counterparty risk increased. Keywords: interbank market, liquidity, interest rates, crisis, risk premia, credit risk, liquidity risk, counterparty risk JEL classification: G190, G210
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Stress Testing of the Banking Sector in Emerging Markets A Case of the Selected Balkan Countries
Vukelić, Tatjana ; Jakubík, Petr (advisor) ; Mejstřík, Michal (referee)
Stress testing is a macro-prudential analytical method of assessing the financial system's resilience to adverse events. This thesis describes the methodology of the stress tests and illustrates the stress testing for credit and market risks on the real bank-by-bank data in the two Balkan countries: Croatia and Serbia. Credit risk is captured by the macroeconomic credit risk models that estimate the default rates of the corporate and the household sectors. Setting-up the framework for the countries that were not much covered in former studies and that face the limited availability of data has been the main challenge of the thesis. The outcome can help to reveal possible risks to financial stability. The methods described in the thesis can be further developed and applied to the emerging markets that suffer from the similar data limitations. JEL Classification: E37, G21, G28 Keywords: banking, credit risk, default rate, macro stress testing, market risk
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Discrimination measures in credit risk
Polak, Michal ; Pešta, Michal (advisor) ; Zahradník, Petr (referee)
Scoring models represent a fundamental tool for the modern management of credit risk. This is mainly due to a significant development in the field of information technology. Such models are used not only when providing credit, but also in strategies relating to the future management of credit risk, or in strategies connected with enforcing receivables. In my thesis I deal with discrimination measures used in the validation of diversification potential of logistic scoring models. At the beginning, I focus on the term 'risk'. Then, I introduce a basic division of scoring models. Next, I describe the method of scoring logistic regression, I concentrate on estimating parameters, their significance and on testing their relevance. For the measurement and illustration of diversification potential of the model I mention the most commonly used methods such as the Lorenz and ROC curve, the Gini coeficient, the c-statistic as well as the Kolmogorov-Smirnov test. Finally, I apply the theoretical knowledge to real data. I design a scoring model and subsequently compare the discrimination measures which it contains. Powered by TCPDF (www.tcpdf.org)
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