This master’s thesis has aimed to contribute and fill the gap in existing studies and research where there has been a lack of knowledge about the relationship between credit ratings and stock recommendations. The purpose of this study is to analyse whether credit ratings from credit rating agencies affect financial analysts’ recommendations, as well as the opposite, if financial analysts’ recommendations affect credit rating agencies' credit ratings. The thesis has used quantitative methods with both panel data regressions where credit rating has been the dependent variable, as well as logistic regressions where recommendation has been the dependent variable. The data set has been based on firms Moody’s has issued credit ratings to between the years 1994 and 2016. The thesis’ results show that both the credit ratings from credit rating agencies and recommendations from financial analysts do indeed affect each other. This concludes that the two-way mirror between credit ratings and recommendations does exist.

This thesis deals with the development, implementation and application of statistical modeling techniques which can be employed in the analysis of credit ratings. Credit ratings are one of the most widely used measures of credit risk and are relevant for a wide array of financial market participants, from investors, as part of their investment decision process, to regulators and legislators as a means of measuring and limiting risk. The majority of credit ratings is produced by the "Big Three" credit rating agencies Standard & Poors', Moody's and Fitch. Especially in the light of the 2007-2009 financial crisis, these rating agencies have been strongly criticized for failing to assess risk accurately and for the lack of transparency in their rating methodology. However, they continue to maintain a powerful role as financial market participants and have a huge impact on the cost of funding. These points of criticism call for the development of modeling techniques that can 1) facilitate an understanding of the factors that drive the rating agencies' evaluations, 2) generate insights into the rating patterns that these agencies exhibit. This dissertation consists of three research articles. The first one focuses on variable selection and assessment of variable importance in accounting-based models of credit risk. The credit risk measure employed in the study is derived from credit ratings assigned by ratings agencies Standard & Poors' and Moody's. To deal with the lack of theoretical foundation specific to this type of models, state-of-the-art statistical methods are employed. Different models are compared based on a predictive criterion and model uncertainty is accounted for in a Bayesian setting. Parsimonious models are identified after applying the proposed techniques. The second paper proposes the class of multivariate ordinal regression models for the modeling of credit ratings. The model class is motivated by the fact that correlated ordinal data arises naturally in the context of credit ratings. From a methodological point of view, we extend existing model specifications in several directions by allowing, among others, for a flexible covariate dependent correlation structure between the continuous variables underlying the ordinal credit ratings. The estimation of the proposed models is performed using composite likelihood methods. Insights into the heterogeneity among the "Big Three" are gained when applying this model class to the multiple credit ratings dataset. A comprehensive simulation study on the performance of the estimators is provided. The third research paper deals with the implementation and application of the model class introduced in the second article. In order to make the class of multivariate ordinal regression models more accessible, the R package mvord and the complementary paper included in this dissertation have been developed. The mvord package is available on the "Comprehensive R Archive Network" (CRAN) for free download and enhances the available ready-to-use statistical software for the analysis of correlated ordinal data. In the creation of the package a strong emphasis has been put on developing a user-friendly and flexible design. The user-friendly design allows end users to estimate in an easy way sophisticated models from the implemented model class. The end users the package appeals to are practitioners and researchers who deal with correlated ordinal data in various areas of application, ranging from credit risk to medicine or psychology.

This thesis concerned with certain problems in the U.S. financial market during the financial crisis. In the theoretical part of this thesis, I deal with the formation of U.S. banking and regulation and supervision until its present form. In this part of the work are described in detail circumstances that lead to foundation of the Federal Reserve system, and also the origins of Great Depression. The practical part is focused on the analysis of the causes of the global financial crisis. Especially the U.S. real estate market, asset securitization and credit rating agencies. In the final part of this work are described in detail the measures taken by the U.S. government in the form of law "Dodd-Frank Wall Street Reform and Consumer Protection Act".

The main aim of this diploma thesis is to analyze benefits of the establishment of the European Rating Agency. The partial aim is to determine the influence of the credit ratings on economics situation in selected European countries and to analyze problems of current credit rating industry. A slight impact of the credit ratings on the observed countries has been found by way of the analysis of evolution of the yields of ten-year government bonds and the prices of CDS contracts on these bonds. Non-perfect competition, weak transparency of the rating process and conflict of interest are considered as the most important problems of the credit rating agencies. By way of the analysis of the ability of the European Rating Agency to remove or at least to partially eliminate discussed problems has been found that the European Rating Agency would not be able to remove all problems of the credit rating industry. The uncertainty about the independence of the European Rating Agency is the biggest weakness of this agency. For this reason, we can't expect that the European Rating Agency would be able to make the credit rating process more efficient and improve the situation in the credit rating industry.

This thesis consists of four independent chapters on bank capital regulation and the issue of unsolicited ratings.<p><p>The first chapter is introductory and reviews the motivation for regulating banks and credit rating agencies while providing a detailed overview of the thesis.<p><p>The second chapter uses a simultaneous equations model to analyze how banks from six G10 countries adjusted their capital to assets ratios and risk-weighted assets to assets ratio between 1988 and 1995, i.e. just after passage of the 1988 Basel Accord. The results suggest that regulatory pressure brought about by the 1988 capital standards had little effect on both ratios for weakly capitalized banks, except in the US. In addition, the relation between the capital to assets ratios and the risk-weighted assets to assets ratio appears to depend not only on the level of capitalization of banks, but also on the countries or groups of countries considered.<p><p>The third chapter provides Monte Carlo estimates of the amount of regulatory capital that EMU banks must hold for their corporate, bank, and sovereign exposures both under Basel I and the standardized approach to credit risk in Basel II. In the latter case, Monte Carlo estimates are presented for different combinations of external credit assessment institutions (ECAIs) that banks may choose to risk weight their exposures. Three main results emerge from the analysis. First, although the use of different ECAIs leads to significant differences in minimum capital requirements, these differences never exceed, on average, 10% of EMU banks’ capital requirements for corporate, bank, and sovereign exposures. Second, the standardized approach to credit risk provides a small regulatory capital incentive for banks to use several ECAIs to risk weight their exposures. Third, the minimum capital requirements for the corporate, bank, and sovereign exposures of EMU banks will be higher in Basel II than in Basel I. I also show that the incentive for banks to engage in regulatory arbitrage in the standardized approach to credit risk is limited.<p><p>The fourth and final chapter analyses the effect of soliciting a rating on the rating outcome of banks. Using a sample of Asian banks rated by Fitch Ratings, I find evidence that unsolicited ratings tend to be lower than solicited ones, after accounting for differences in observed bank characteristics. This downward bias does not seem to be explained by the fact that better-quality banks self-select into the solicited group. Rather, unsolicited ratings appear to be lower because they are based on public information. As a result, they tend to be more conservative than solicited ratings, which incorporate both public and non-public information.<p> / Doctorat en sciences économiques, Orientation économie / info:eu-repo/semantics/nonPublished

This thesis deals with globalisation of markets. It focuses on examining the economic crisis of 2008 and 2010 and on how individual countries can cope with deteriorating of macroeconomic values, especially with financial implications of this situation. The thesis also examines credit rating agencies as indicators of financial soundness of investment instruments, to which is often reffered as to culprits of the crisis for their reaction to the development of the mortgage market. The thesis defines the rating in the concept of sovereign states and describes the market of credit rating agencies. It further evaluates individual rating agencies and practices in the context of the crisis, bringing a comprehensive picture of the role they played at the beginning of the crisis. It also attempts to outline more points of view on the previously unilaterally and predominantly negatively perceived issue of reputation of credit rating agencies.