This master thesis deals with the issue of using rating in the context of determining capital requirements. The focus is on using the Standardised Approach and the Internal Rating-Based Approach to calculate credit risk capital requirements. Different approaches to managing the risk and evaluating the capital adequacy. Criticism of rating agencies as well as the complexity of Internal Rating-Based Approach is taken into account. Furthermore, the thesis discusses the issue of responsibility of external rating agencies for their evaluations, and together with the issue of lacking competition. Various alternatives to external rating are discussed. The internal rating process is discussed in more detail along with the factors which affect rating evaluations of exposures to various entities. Subsequently, the thesis focuses on determining the rate of provision for impairment expected losses on receivables, and a possible impact of accepting IFRS 9 on capital adequacy.

This dissertation proposes stress testing of a bank’s corporate credit portfolio in a Basel Internal Ratings Based (IRB) framework, using publicly available macroeconomic variables. Corporate insolvencies are used to derive a credit cycle index, which is linked to macroeconomic variables through a multiple regression model. Probability of default (PD) and loss given default (LGD) that are conditional on the worst state of the credit cycle are derived from through-the-cycle PDs and LGDs. These are then used as stressed inputs into the Basel regulatory and Economic capital calculation for credit risk. Contrary to the usual expert judgement stress testing approaches, where management apply their subjective view to stress the portfolio, this approach allows macroeconomic variables to guide the severity of selected stress testing scenarios. The result is a robust stress testing framework using Rösch and Scheule (2008) conditional LGD that is correlated to the stressed PD. The downturn LGD used here is an alternative to the widely used Federal Reserve downturn LGD which assumes no correlation between PDs and LGDs. / Dissertation (MSc)--University of Pretoria, 2014. / gm2014 / Mathematics and Applied Mathematics / Unrestricted

In recent times, credit risk analysis has grown to become one of the most important problems dealt with in the mathematical finance literature. Fundamentally, the problem deals with estimating the probability that an obligor defaults on their debt in a certain time. To obtain such a probability, several methods have been developed which are regulated by the Basel Accord. This establishes a legal framework for dealing with credit and market risks, and empowers banks to perform their own methodologies according to their interests under certain criteria. Credit risk analysis is founded on the rating system, which is an assessment of the capability of an obligor to make its payments in full and on time, in order to estimate risks and make the investor decisions easier.Credit risk models can be classified into several different categories. In structural form models (SFM), that are founded on the Black & Scholes theory for option pricing and the Merton model, it is assumed that default occurs if a firm's market value is lower than a threshold, most often its liabilities. The problem is that this is clearly is an unrealistic assumption. The factors models (FM) attempt to predict the random default time by assuming a hazard rate based on latent exogenous and endogenous variables. Reduced form models (RFM) mainly focus on the accuracy of the probability of default (PD), to such an extent that it is given more importance than an intuitive economical interpretation. Portfolio reduced form models (PRFM) belong to the RFM family, and were developed to overcome the SFM's difficulties.Most of these models are based on the assumption of having an underlying Markovian process, either in discrete or continuous time. For a discrete process, the main information is containted in a transition matrix, from which we obtain migration probabilities. However, according to previous analysis, it has been found that this approach contains embedding problems. The continuous time Markov process (CTMP) has its main information contained in a matrix Q of constant instantaneous transition rates between states. Both approaches assume that the future depends only on the present, though previous empirical analysis has proved that the probability of changing rating depends on the time a firm maintains the same rating. In order to face this difficulty we approach the PD with the continuous time semi-Markov process (CTSMP), which relaxes the exponential waiting time distribution assumption of the Markovian analogue.In this work we have relaxed the constant transition rate assumption and assumed that it depends on the residence time, thus we have derived CTSMP forward integral and differential equations respectively and the corresponding equations for the particular cases of exponential, gamma and power law waiting time distributions, we have also obtained a numerical solution of the migration probability by the Monte Carlo Method and compared the results with the Markovian models in discrete and continuous time respectively, and the discrete time semi-Markov process. We have focused on firms from U.S.A. and Canada classified as financial sector according to Global Industry Classification Standard and we have concluded that the gamma and Weibull distribution are the best adjustment models.

This master thesis deals with the area of commercial bank's external audit in the Czech Republic. Its main goal is to highlight the different techniques and specific procedures which are used during statutory audit of commercial bank. Another goal of this master thesis is to investigate of a linear dependence between count of changes of auditors and selected commercial bank's performance indicators. In the first part we could find a general framework of the external audit with emphasis on legal aspects. The second part describes differences between bank and non-banking institution. The third part of this master thesis deals with a description of audit phases with emphasis on the interim audit phase at which the author of this master thesis was a part of audit providing team. The final part investigates the linear dependence between count of changes of auditors and selected commercial bank's performance indicators.

We propose a Markov chain model for credit rating changes. We do not use any distributional assumptions on the asset values of the rated companies but directly model the rating transitions process. The parameters of the model are estimated by a maximum likelihood approach using historical rating transitions and heuristic global optimization techniques. We benchmark the model against a GLMM model in the context of bond portfolio risk management. The proposed model yields stronger dependencies and higher risks than the GLMM model. As a result, the risk optimal portfolios are more conservative than the decisions resulting from the benchmark model.

This diploma thesis focuses on syndicated loans. It analyzes mostly the development of syndicated loans during last years from different points of view. Special attention is given to the syndicated loan market in Europe and USA. At the beginning of this paper, it is proved, that syndicated loans are important source of corporate financing. Most important characteristics of syndicated loans are mentioned after that. The chapter three deals with pricing of syndicated loans in the theoretical way. Next chapter concerns with trading of syndicated loans in secundary market in the USA. After that, syndicated loans are given to the relevance to credit derivates. Next chapter analyzes different asspects of the development of syndicated loans during last years. The chapter seven empirically proves the impact of financial crisis on syndicated loans market. There is also a comparison of spreads on syndicated loans market in Europe and USA. Last chapter focuses on the relationship between syndicated loans and GDP.

The dissertation compares the export credit rating model of the national Export Guarantee and Insurance Agency EGAP with models applied by selected Czech banks. The first part of the dissertation presents a summary of credit risk theory. It depicts the main principles of lending and its risks. The dissertation further describes the factors that influence credit risk and the methods of its modelling. While mathematical risk models project the expected loss as well as its sensitivity to the risk factors, the focus of this thesis lies in qualitative models which set a normalized scale for probability of default, the so called credit rating models. The main contribution of the dissertation lies in the survey carried out among four Czech banks belonging to owners from various countries, from which we get an overview of their rating models. It follows from the gathered information that their models are based on financial indicators when rating the buyers/exporters. The models are also considerably amended by non-financial factors whose importance in certain cases rose following the recent financial crisis. The agency EGAP insures business activities abroad and therefore its model takes into account also specific factors related to the destination country. The main difference between the models of EGAP and the examined banks lies in the method of creation and validation: EGAP does not dispose of sufficient amount of business case studies, so that it has to rely on external consulting services when setting up and validating the model. The dissertation concludes that while all rating models are composed of similar risk factors highlighting past financial indicators of the financed business, each analysed rating model differs significantly in the specific database of business cases that were used to construct the model, depending on the availability of data to the bank/insurer. The conclusion that can be drawn from this fact is that the main factor for successful prevention of future failures of the credit rating models will be the extent of the credit assessment database which will be used for the construction of the respective rating model.

The subject of this thesis is an analysis of causes and impacts of credit risk transfer through credit derivatives on the world economy. It deals with the theoretical view of credit derivatives and their definition. A significant part of the work is devoted to a description of the current credit derivatives market and to motives for trading them. In the continuous process of derivative products innovation selected types are described. Those types that were spread during last two decades. In another part are introduced credit derivatives market participants and special attention is given to the banking sector. Important part is the description of an economic situation in countries in crisis. The aim of this work is to give a complete description of all sectors that were influenced by credit derivatives market.

The priority of this work is to show the importance of risk management and the proper operation in electricity trading companies. In the theoretical part of the thesis are summarized basic information about the energy market in the Czech Republic and also a brief overview of the risks observed in the electricity trading. In recent years there have been several cases where a company did not observe their risks or even did not monitor these risks at all. This had a negative impact on the entire Czech energy market. In the practical part of this thesis are described the cases of companies Moravia Energo a.s. and Korlea Invest a.s., setting its risk management and also consequences of their falls. Furthermore, this work describes the different tools to support risk management, which are not the cheapest definitely. Also work contains an example of calculating the limits for credit exposure of the two companies that I calculated based on the analysis of the annual reports of these companies and I managed to get a lot of interesting information during writing this work that the reader will definitely appreciate.

The diploma thesis is focused on predictive modeling in credit risk management. Banks and financial institutions are mainly interested in it to estimate the probability of client's default in order to make a decision about which client will be accepted and which client will be rejected. The theoretical part includes an introduction of credit scoring and a description of discrete choice models. The linear probability model, the probit model and the logit model are described in detail. The logit model is afterwards used for the prediction of client's default. The practical part is focused on a statistical description of the dataset and a description of how to work with it before we start with the development of the credit scoring model. After that follows the estimation of the model on testing sample, its testing and the estimation of the model on full sample with a description of individual steps of calculation and outputs of the program SPSS.