Our thesis aims to help the market participants to understand the source of the risk in green bonds market. We estimate the liquidity risk effects in green bonds' yield spreads as well as controlling for credit risk, bond-specific chracteristics and macroeconomic variables. Both of our liquidity measures suggest that green bonds are more liquid than investment grade US corporate bonds. We find that liquidity effect in green bonds' yield spreads is pronounced, and the result is robust after controlling for potential endogeneity bias. The power of green bonds' liquidity premium is about 10 to 100 times as strong as speculative grade German bonds and investment grade US corporate bonds respectively. In addition to the lack of clear risk profile in green bonds market, our three-stage least squares regression shows that credit risk influences the liquidity risk of green bonds, this indicates that credit risk is a potential source of private information that affects the high liquidity of green bonds. This result has an implication for policy as the credit risk and liquidity risk could be the pitfalls in green bonds market.

Understanding the determinants of aggregated default probabilities (PDs) has attracted substantial research over the past decades. This study addresses two major difficulties in understanding the determinants of aggregate PDs: Model uncertainty and multicollinearity among the regressors. We present Bayesian Model Averaging (BMA) as a powerful tool that overcomes model uncertainty. Furthermore, we supplement BMA with ridge regression to mitigate multicollinearity. We apply our approach to an Austrian dataset. Our findings suggest that factor prices like short term interest rates and energy prices constitute major drivers of default rates, while firms' profits reduce the expected number of failures. Finally, we show that the results of our baseline model are fairly robust to the choice of the prior model size. / Series: Research Report Series / Department of Statistics and Mathematics

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

The aim of this thesis is to investigate possible improvement of scoring models prediction power in retail credit segment by using structural models estimating the future development of behavioral score. These models contain the informa- tion about past development of the behavioral score by parameters which take into account the sensitivity of clients' probability of default on individual market and life changes. These parameters are estimated by Markov Chain Monte Carlo methods based on score history. Eight different types of structural models were applied to real data. The diversification measure of individual 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

The aim of this thesis is to address the implications of Basel III regulation on counterparty credit risk. We analysed the development of OTC market, we addressed systemic risk and the way how central counterparties could mitigate or spread the contagion among banks. We used simulated data to develop a stress test model to find out the impact of counterparty credit risk on banks' capital requirements, in case the interest rate increased extensively. Six pos- sible scenarios of interest rate levels were developed with ascending order of the IR level. From these scenarios we computed the exposure levels and credit valuation adjustment (CVA) as the market value of counterparty credit risk. We came to the following conclusions: (1) Czech banks have enough capital to withstand any interest rate increase in any scenario. (2) Banks with high expo- sure to derivatives like Bank of America, Citibank and JP Morgan would face severe problems if the interest rate increased. (3) There is no direct correlation between credit valuation adjustment and interest rate, the CVA increases faster with the increase of the interest rate.

Master Thesis - Simona Tothova Abstract This thesis empirically investigates impact of countries' bailouts on probability of SME segment distress. The impact is examined by multi-period logit model where dependent variable is distress rate and explanatory variables includes self-constructed bailout variable, several binary predictors and firm-specific and macroeconomic control variables. The hypotheses are tested on dataset for period from 2005 to 2013 including observations from seven European countries which received financial assistance program (bailout) from Troika. Every bailout from Troika comes with the requirement for austerity measures and our results suggest that impact of bailouts on SMEs probability of distress are depended on the success of application in individual countries and the impacts are more positive in non euro-zone countries. Keywords Bailout, Financial crisis, Credit risk, SME segment, Distress rate Author's e-mail tothova.simona@gmail.com Supervisor's e-mail rado.parrak@gmail.com

Counterparty credit risk is an important type of financial risk. The importance of proper counterparty risk management became most apparent in the wake of the 2008 series of failures of several large banks. Correlation of market factors is an important issue in the calculation of CVA. A notable case of correlation is wrong-way risk which occurs whenever the probability of default of the counterparty is positively correlated with exposure. The basic formulas for CVA and basic counterparty credit risk models do not account for wrong-way risk because its modeling is nontrivial. This thesis aims to answer how well can the impact of wrong-way risk on CVA be approximated with an add-on which only depends on correlation between the price of the underlying asset and the credit spread of the counterparty. The thesis is supplemented by a fully documented implementation of the model in the Mathematica software.

The thesis is focused on the options of quantifying credit risk by using the concept of the KMV model. The introduction outlines the basic approaches to measuring credit risk. In the following chapters is specified the nature of KMV model with the focus on its application in the Czech capital market. Self-calibration of the KMV model is made in this part. The analytical part related to the quantification of credit risk using the KMV model is implemented on selected companies which are traded on the Prague Stock Exchange. The results obtained are consequently confronted with the official rating degrees of agency Moody's.

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...

Les systèmes d’information bancaires, outils incontournables de la stratégie des banques, sont devenus complets et complexes. Et les systèmes d’information décisionnels ou stratégiques deviennent de plus en plus présents.Or, il persiste encore des inefficacités en matière de conception des systèmes d’informations, dues à une conception sauvage ou plutôt une construction sauvage des systèmes d’informations stratégiques, avec une mise à l’écart systématique des utilisateurs finals.Une solution parait être de s’appuyer sur l’intelligence économique pour tenter de résoudre le problème de la construction de ces systèmes d’information stratégiques, et donc d’améliorer la prise de décision. Car, le système d’informations stratégique, noyau des systèmes décisionnels, est le cœur même du système d’intelligence économique.Notre thèse est qu’une démarche d’intelligence économique appliquée à la conception des systèmes d’informations bancaires permettrait de réduire le « risque prêt ». Ceci, précisément, dans le domaine de la banque de détail et pour la clientèle des particuliers, des professionnels et des entrepreneurs.- Risque pour le client qui ne doit pas se lancer dans des remboursements qu’il ne pourra assumer, s’engager dans un projet de prêt qui ne correspondrait pas aux enjeux qu’il s’est définis ;- Risque évidemment pour la banque qui ne tient pas à accumuler des clients non solvables et ce qui ne correspondrait pas non plus à des enjeux définis par les décideurs de la banque.Après avoir rappelé les particularités de la banque et la complexité de son environnement, nous montrerons en quoi l'approche actuelle de la gestion des risques au sein des banques nous paraît « incomplète » et segmentée, et de ce fait, perfectible notamment pour ce qui concerne la clientèle des particuliers et des professionnels. Ensuite, nous comptons proposer des règles méthodologiques pour la conception de systèmes d’informations stratégiques bancaires, ainsi qu’un modèle d’architecture d’un tel système prenant en compte les besoins de l’utilisateur final qui sera, dans le cas de notre thèse, le décisionnaire d’un dossier de crédit ou bien le conseiller bancaire, voire l’analyste du risque de crédit. Enfin, après avoir établi ce modèle d'architecture de système d’informations stratégiques, nous comparerons ce qu'il permettrait d'améliorer, relativement à l'existant. Notre thèse se situe au carrefour, au confluent, d'une thèse en sciences de gestion, plus particulièrement en finance bancaire, et d’une thèse en système d'informations et en informatique ; et elle s’appuie en grande partie sur notre expérience professionnelle dans le secteur bancaire en France.Ainsi, avec le domaine bancaire, nous souhaitons explorer un nouveau domaine d’application des recherches en intelligence économique, notamment en liaison avec les résultats issus des travaux de l’équipe de recherches SITE (« Modélisation et Développement de Systèmes d’Intelligence Economique ») du LORIA (Laboratoire Lorrain de Recherches en Informatique et ses Applications) pour ce qui concerne la conception de systèmes d’informations pour l’intelligence économique.Après avoir présenté le concept d’intelligence économique et le processus décisionnel, nous montrerons les spécificités de la banque et de son système d’informations. Ensuite, nous expliciterons les difficultés de la gestion du risque de crédit au sein des banques avant de présenter nos propositions pour la mise en place d’un système d’informations stratégiques permettant d’améliorer la gestion du risque de crédit bancaire. / Bank Information Systems, key tools in banking strategies, have become comprehensive and complex. And the decision-making or strategic information systems are playing an increasingly more important role.Nevertheless, some inefficiencies in the conception of information systems still continue to exist, due to the uncontrolled design or rather construction of strategic information systems, systematically alienating the end-user.One solution seems to be to rely on economic intelligence to attempt to solve the matter of the construction of those strategic information systems, and consequently to improve decision-making. Because, the strategic information system, the core of decision-making systems, is the heart itself of the economic intelligence system.Our theory is that an approach of economic intelligence applied to the conception of information systems in banking would allow the reduction of the “loan risk”. This specifically in the sector of retail banking and for the individual, professional and contractor customer.- Risk for the customer who should not start loan payments which he cannot cover, or commit to loan projects which do not match the stakes he would have set himself.- Risk obviously for the bank which is not willing to accumulate uncreditworthy customers, and which would not match either the stakes set by the bank decision-makers.After putting emphasis on the distinctive features of the bank and the complexity of its environment, we will show the evidence that the current approach to risk management inside banks seems “incomplete” and fragmented, and consequently, where there is room for improvement particularly for individual and professional customers.Then, we intend to suggest some methodological rules for the conception of strategic information systems in banking, as well as a business model of such a system taking into account the needs of the end-user who will be, as shown in this present thesis, the decision-maker of a credit file or the bank adviser, or even the credit risk analyst. Finally, after drawing up this model of strategic information systems, we will compare how it could improve on the existing one. Our thesis is situated at a crossroads, at a confluence, of a thesis in management sciences, more particularly in bank finance, and of a thesis in information systems, and in computer science; and it leans largely on our professional experience in the banking sector in France.Thus, along with the banking sector, we wish to explore the new field of application of research in economic intelligence, particularly linked to the results stemming from the work by the research team SITE of LORIA as far as the conception of information systems for economic intelligence is concerned.After introducing the concept of economic intelligence and the decision-support process (chapter no. 1), we will outline the specificities of the banking sector and its information systems (chapter no. 2). Then we will clarify the difficulties of credit risk management within banks (chapter no. 3) before submitting our proposals for the implementation of a strategic information system enabling the improvement of credit risk management in banking (chapter no. 4).