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Výpočet korelace v úvěrovém portfoliu a její vliv na celkové kreditní riziko portfolia
Pacovský, Matěj ; Kopa, Miloš (advisor) ; Dostál, Petr (referee)
In recent years many works employed the topic of the estimation of the asset value correlation from the portfolio of debtors and their properties. The results vary depending on the methods used or the data sets, on which the model was applied. The Master Thesis describes the methods of estimation of the asset value correlation from 5-year default performance of small and medium-sized enterprise (SME) debtors of Komercni Banka. Each method is firstly described in detail and then applied. Estimations of the asset value correlation are performed in rating and industrial homogeneous group. The conclusion contains a comparison of resulting capital with a former Basel correlation and the capital when our estimations of the asset correlation are used as a parameters. Powered by TCPDF (www.tcpdf.org)
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Three Essays on Bank-Sourced Credit Risk Estimates
Štěpánková, Barbora ; Krištoufek, Ladislav (advisor) ; Teplý, Petr (referee) ; Seow, Hsin-Vonn (referee) ; Ansell, Jake (referee)
The aim of the thesis is to bring new insights into banks' internal credit risk estimates and their application in estimation of credit transition matrices, which are an important part of credit risk modelling with limited publicly available sources. The doctoral thesis consists of three essays that jointly analyse features of bank- sourced credit risk data and practicalities of transition matrices estimation. In the first essay, I empirically test two assumptions widely used for estimation of transition matrices: Markovian property and time homogeneity. The results indicate that internal credit risk estimates do not satisfy the two assumptions, showing evidence of both path-dependency and time heterogeneity even within a period of economic expansion. Contradicting previous findings based on data from credit rating agencies, banks tend to revert their past rating actions. The second essay analyses the extent to which transition matrices depend on the characteristics of the underlying overlapping bank-sourced credit risk datasets and the aggregation method. It outlines that the choice of aggregation approach has a substantial effect on credit risk model results. I also show that bank-sourced transition matrices are more dynamic than those produced by credit rating agencies and introduce industry-specific...
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Effects of LTV, DTI and DSTI ratios on retail mortgage market. Evidence from the Czech Republic
Mičková, Anna ; Pečená, Magda (advisor) ; Hanus, Luboš (referee)
The thesis analyses the effects of credit-related borrower-based macroprudential measures - loan-to-value (LTV), debt-to-income (DTI) and debt service-to-income (DSTI) ratios - on retail mortgage market in the Czech Republic. These lending instruments, which target mainly borrowers and restrict the amount of money borrowed relative to the value of underlying collateral (LTV) or client's disposable income (DTI, DSTI), represent a non-negligible part of macroprudential policy. This entry barrier should act in a preventive manner to protect borrowers from taking high-amount and high-risk mortgages and eventually curb excessive private sector leverage. After the introduction and implementation of limits in the Czech Republic, the supply of loans with risky parameters declined, the share of non-performing mortgage loans decreased, and the rise in house price index decelerated. In 2019, the volume of new mortgage loans declined by 13.6 % year-over-year compared to the previous year and the spiral between increasing credit financing of property purchases and rising property prices slightly weakened.
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Komerční banky: Měření kreditního rizika interním ratingem bank
Kolínková, Vendula
Kolínková, V. Commercial banks: Measurement of credit risk by internal bank ratings. Bachelor thesis. Brno: Mendel University, 2018. This Bachelor thesis deals with an analysis of the current state of credit risk management approaches of commercial banks and defines advantages and disadvantages of Standardized approach and IRB approach. Using the regulation (EU) No 575/2013 of the European Parliament and of the Council deals in detail with the legislation of these approaches. This analysis implies that banks have to use several factors to assess the IRB approach contribution in the form of capital savings or a relatively simple calculation of the Standardized approach.
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Bank credit risk management in the low-interest rate environment
Maivald, Matěj ; Teplý, Petr (advisor) ; Pečená, Magda (referee)
The thesis examines the relation of the low-interest rate environment to the banks' selected credit risk measures with a panel dataset on banks in Eurozone, Denmark, Japan, Sweden, and Switzerland covering the period 2011-2017. It employs a system GMM framework and a combination of bank-related and macroeconomic variables. This study builds on recent literature on effects of low-interest rates on banks' profitability and estimates the following three hypotheses: The potential effects of the low-interest rate on non-performing loans (NPL) ratio, risk-weighted assets (RWA) to total assets ratio, and changes in Tier 1 capital ratio. There are three main results: Firstly, the results suggest that a prolonged period of negative monetary interest rate can affect the NPL ratio and reveal a possible relationship between the 3M-interbank interest rate and NPL ratio. Thus, the thesis does not reject the first hypotheses. However, it rejects these hypotheses in case of the other two ratios. Secondly, the study finds a bank heterogeneity to be a significant determinant of the credit risk. Finally, using recent data, this thesis contributes to the literature focusing on the drivers of the NPL ratio, RWA to total assets ratio and Tier 1 capital ratio, where in case of the latter two the existing research is...
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Satellite Model Accuracy in Bank Stress Testing
Hamáček, Filip ; Polák, Petr (advisor) ; Pečená, Magda (referee)
Satellite Model Accuracy in Bank Stress Testing Abstract Filip Hamáček January 4, 2019 This thesis is dealing with credit risk satellite models in Czech Republic. Satellite model is a tool to predict financial variable from macroeconomic vari- ables and is useful for stress testing the resilience of the banking sector. The aim of this thesis is to test accuracy of prediction models for Probability of De- fault in three different segments of loans - Corporate, Housing and Consumer. Model currently used in Czech National Bank is fairly unchanged since 2012 and its predictions can be improved. This thesis tests accuracy of the original model from CNB by developing new models using modern techniques, mainly by model combination methods: Bayesian Model Averaging (currently used in European Central Bank) and Frequentist Model Averaging. Last approach used are Neural Networks. 1
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Ensemble learning methods for scoring models development
Nožička, Michal ; Witzany, Jiří (advisor) ; Cipra, Tomáš (referee)
Credit scoring is very important process in banking industry during which each potential or current client is assigned credit score that in certain way expresses client's probability of default, i.e. failing to meet his or her obligations on time or in full amount. This is a cornerstone of credit risk management in banking industry. Traditionally, statistical models (such as logistic regression model) are used for credit scoring in practice. Despite many advantages of such approach, recent research shows many alternatives that are in some ways superior to those traditional models. This master thesis is focused on introducing ensemble learning models (in particular constructed by using bagging, boosting and stacking algorithms) with various base models (in particular logistic regression, random forest, support vector machines and artificial neural network) as possible alternatives and challengers to traditional statistical models used for credit scoring and compares their advantages and disadvantages. Accuracy and predictive power of those scoring models is examined using standard measures of accuracy and predictive power in credit scoring field (in particular GINI coefficient and LIFT coefficient) on a real world dataset and obtained results are presented. The main result of this comparative study is that...
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Comparison of statistical methods for the scoring models development
Mrázková, Adéla ; Vitali, Sebastiano (advisor) ; Kopa, Miloš (referee)
The aim of this thesis is to introduce and summarize the process of scoring model development in general and then basic statistical approaches used to resolve this problem, which are in particular logistic regression, neural networks and decision trees (random forests). Application of described methods on a real dataset provided by PROFI CREDIT Czech, a.s. follows, including discussion of some implementation issues and their resolution. Obtained results are discussed and compared.
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Credit risk management
Sobolčik, Lukáš ; Kislingerová, Eva (advisor) ; Smrčka, Luboš (referee)
The goal of the Master`s thesis is the credit risk analysis of existing corporation done from the point of view of a fictitious multinational corporation which operates in petrochemical business. At first, it deals with general definition of credit risk, tools for its management and methods for its elimination. Later, in the analytical section on an example of concrete model from practice modern trends in credit risk management are demonstrated, potential obstacles are analyzed and the most frequent problems with its application are noted. The main asset of the thesis is a comprehensive introduction of actual credit risk management system supplemented with own observations and experience. The outcome is an educational material for people with interest in given topic as well as for professionals in the field of credit risk management.
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Regulatory Approaches to Credit Risk Quantification
Stará, Pavla ; Pečená, Magda (advisor) ; Hausenblas, Václav (referee)
Credit risk represents one of the most significant risks which a bank must face, and therefore, its intention is effectively manage and measure this risk. However, management and measurement methods are supervised and influenced by national regulators. Banking regulatory supervision plays a significant role among others in determining minimum capital requirements that serve as buffer against losses stemming from credit risk. This thesis provides theoretical foundation of regulatory approaches - standardized and internal rating based (IRB) approach - used for quantification of regulatory capital to credit risk as well as empirical application of such approaches on created portfolio of corporate loans. As a part of IRB method I suggested a model composed of financial ratios estimating probability of default using logistic regression. I founded out that rather the use of combination of financial ratios from different groups of ratios with slight dominance of profitability ratios forms final model. Therefore, superiority of solvency ratios in modelling cannot be proved on my portfolio. After estimating and determining necessary parameters I quantified the minimum regulatory capital requirements to credit risk under standardized and IRB approaches prescribed by Basel III. In the end, the results are...
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