Práce podrobně charakterizuje a analyzuje strukturální modely kreditního rizika. Nejprve je vymezena základní myšlenka strukturálních modelů, která je spojena s pracemi Blacka, Scholese (1973) a Mertona (1974). Následuje rozšíření v podobě first-passage-time modelů jak s konstantní, tak se stochastickou úrokovou sazbou. Dále je zmíněn i Zhou (1997) model a empirická verifikace a využití strukturálních modelů. Na závěr jsou některé strukturální modely aplikovány na společnosti Telecom a ČEZ.

This master thesis discusses alternative debt management instruments - GDP-linked bonds. It provides concise characterization of sovereign debt management. Additionally, it discusses traditional derivatives, such as futures, swaps and bonds, from the government's point of view. The main goal of the thesis is to verify whether GDP-linked bonds are suitable for the Czech and Slovak debt management. Ergo, the bonds could smooth the cost of serving the debt. Furthermore, it describes the development of the sovereign debt and risk premium of the government bonds of the Czech and Slovak republics. It tries to find out whether the risk premium of Slovak bonds differed after introduction of euro. Additionally, the thesis analyzes the effect of various country specific variables on the development of the risk premium. The last but not least goal is to support or reject the hypothesis whether the GDP-linked bonds should be appealing to European economic and monetary union as the members has to satisfied Stability and Growth Pact requirements. The conclusion of the thesis is that the hypothesis of positive effect of the GDP-linked bonds on the cost of serving debt is partly rejected in case of the Czech and Slovak republics as well as in the case of European economic and monetary union. Furthermore, the risk...

This thesis is devoted to UK Mortgage Performance Modelling. The research conducted uses an option pricing methodology to model theoretically the value of Mortgages, the Option to default and the probability to default and to compare the predictive accuracy of the latter with the predictive accuracy of data driven credit-scoring techniques. Theoretical models are constructed to represent the life cycles of loans collateralised by real property operating within a stochastic economic environment of house-price and interest rate. These realistic mortgage models provide a confirmation of recent research based upon a relaxation of the assumption of financially rational, 'ruthless' prepayment, bridge a potential oversight in existing research by an extension of existing modelling in the stochastic behaviour of the house price process and present a proposal for a straightforward approach utilising characteristic measures of borrower delinquency and insolvency that enables estimation of the default probabilities implicit in residential mortgages using a simple but enhanced optimising structural model. This model straightforwardly demonstrates that one can predict the probability of eventual default, beginning at the origination of the loan, the time when a lender would be most interested in making such a determination. Secondly the problem of mortgage loan default risk is empirically assessed in a number of different ways focusing upon analysis of the competing risks of early termination, the inclusion of macro-economic variables - time varying covariates and unobserved borrower heterogeneity. Key insight is provided by means of a multi-period model exploiting the potential of the survival analysis approach when both loan survival times and the various regressors are measured at discrete points in time. The discrete-time hazard model is used as an empirical framework for analysing the deterioration process leading to loan default and as a tool for prediction of the same event. Results show that the prediction accuracy of the duration model is better than that provided by a single period logistic model. The predictive power of the discrete time survival analysis is enhanced when it is extended to allow for unobserved individual heterogeneity (frailty).

The Basel Accord regulates risk and capital requirements to ensure that a bank holds capital proportional to the exposed risk of its lending practices. Basel II allows banks to develop their own empirical models based on historical data for probability of default (PD), loss given default (LGD) and exposure at default (EAD). Brazil was among the first emerging market countries to release a timetable for the implementation of the Basel II Accord and aimed to apply it uniformly to all Brazilian financial institutions from 2005 to 2011. Within this context, the necessity arises of conducting research that could assist the financial institutions in improving the accuracy of their models. This thesis has three objectives. The first is to develop a macro-economic model to predict the behaviour of the aggregate delinquency in Brazilian consumer loans. The model consists in testing co-integrating relationships and then estimating a short run error correction model. The results based on monthly data from 2000 to 2012 show that the delinquency rate is particularly sensitive to shocks on GDP and to the variation of workers' income. The analysis then shifts to micro or account level to model the behaviour of borrowers and certain novel types of information that can be used for prediction. Second, customers fail to make loan repayments for a number of reasons, ranging from simple forgetfulness to deliberate attempts. For this reason, the second objective is to investigate the reasons for default and to explore ways of incorporating these variables into Recovery Rate (RR = 1 - LGD) models, since the standard approach overlooks real reasons for default and uses proxies for them such as marital status and length of employment. Customers who failed to repay their loans were interviewed in order to discover the causes for this failure. In addition, the interviews included questions aimed to measure the customer's personality traits and their financial knowledge in relation to the reasons for default. The empirical results show that the variables proposed in this study, namely, reason for missing payment, financial knowledge and risk taken, improve the prediction of the recovery rate. Thirdly, it is known that recovery depends on the debt collection process and on the different options or actions that collection departments can take. Yet there is practically no literature exploring the impact of the lender's collection actions on RR/LGD. This work fills this gap by investigating the role of different collection actions at the loan-level for a retail credit product, and by estimating LGD models using Panel Data regressions.

Defaulted retail mortgage loans as a percentage of retail mortgage loans and advances averaged 9 percent over 2010 as reported in the SARB Bank Supervision Annual report. Banks are in the business of risk taking and as a result need to constantly evaluate and review credit risk management to attain sustained profitability. In credit risk modelling, default risk is associated with client-specific factors particularly the client’s credit rating. However, Brent, Kelly, Lindsey-Taliefero, and Price (2011), have shown that variation in mortgage delinquencies reflect changes in general macroeconomic conditions. This study aims to provide evidence of whether macroeconomic factors such as the house price index, CPI, credit growth, debt to income ratio, prime interest rates, and unemployment, are key drivers of residential mortgage delinquencies and default in South Africa. In this study, data from an undisclosed bank is used to estimate three models that are supposed to capture the influence of several macroeconomic variables on 30 day, 60 day, and 90 day delinquency rates over the 2006-2010 period. In order to eliminate the potential bias introduced by those observations, a fourth model was estimated using aggregated banking industry published by the SARB. However, due to data constraints, only the severe mortgage delinquency state, that is the 90 day delinquency rate was modelled using this aggregate data. The SARB sample covers the period between 2008 and 2010. The choice of the date 2008 coincides with the introduction of the Basel 2 regulatory framework. Prior to 2008, the big four South African banks were governed by the Basel 1 framework, and measured their credit risk using the so-called Standardised Approach which has different loan categories and different default definitions compared to the Basel 2 Advanced Internal Ratings Approach adopted in 2008. The findings suggest that the two samples (i.e. the data from the individual bank and the SARB data) imply different explanatory macroeconomic factors. Prime interest rates were found to be the only important variable in determining 30 day and 60 day delinquency rates for the individual bank. The house price index, CPI, credit growth, and prime interest rates were found to be the main determinants of the 90 day delinquency rates for the undisclosed bank, while the house price index, CPI, and credit growth, determine the 90 day delinquency rates for the big four banks.

The focus of this dissertation is the European Credit Default Swaps (CDSs) market. CDSs are the most popular credit derivative products. Three issues are discussed, the first, which is covered in chapter 2, is the investigation of non-diversifiable jump risk in iTraxx sector indices based on a multivariate model that explicitly admits discrete common jumps for an index and its components. Our empirical research shows that both the iTraxx Non-Financials and their components experience jumps during the sample period, which means that the jump risks in the iTraxx sector index are not diversifiable. The second issue, which is covered in chapter 3 is the component structure of credit default swap spreads and their determinants. We firstly extract a transitory component and a persistent component from two different maturities of the Markit iTraxx index and then regress these components against proxies for several commonly used explanatory variables. Our results show that these explanatory variables have significant but differing impacts on the extracted components, which indicates that a two-factor formulation may be needed to model CDS options. The last issue, which is covered in chapters 4, 5 and 6 is the investigation of the linkage between the credit default swap market and the equity market within the European area. We innovatively calibrate the CDS option with the Heston Model to get the implied volatility in the CDS market, which allows us to investigate both the characteristic of implied volatility in the CDS market and the relationship of the two markets not only on the level of daily changes but also with regard to its second moment. Our analysis shows that the stock market weakly leads the CDS market on daily changes but for implied volatility, the stock market leads the CDS market. A VECM analysis shows that only the stock market contributes to price discovery. For sub-investment grade entities, the interactivities between the implied volatility of the CDS market and the implied volatility of the stock market are stronger, especially during the recent credit crunch period. All these results have important implications for the construction of portfolios with credit-sensitive instruments.

This thesis is a collection of three essays in empirical studies on derivatives. In the first chapter, I investigate whether credit default swap spreads are affected by how the total risk is decomposed into the systematic risk and the idiosyncratic risk for a given level of the total risk. The risk composition is measured by the systematic risk proportion, defined as the proportion of the systematic variance in the total variance. I find that a firm’s systematic risk proportion has a negative and significant effect on its CDS spreads. Moreover, this empirical finding is robust to various alternative specifications and estimations. Therefore, the composition of the total risk is an important determinant of CDS spreads. In the second chapter, I estimate the illiquidity premium in the CDS spreads based on Jarrow’s illiquidity-modified Merton model using the transformed-data maximum likelihood estimation method. I find that the average model implied CDS illiquidity premium is about 15 basis points, accounting for 12% of the average level of the CDS spread. I further investigate how this parameter is affected by CDS liquidity measures such as the percentage bid-ask spread and the number of daily CDS spreads available in one month. I find that both liquidity measures are significant determinants of the model implied CDS illiquidity premium. In terms of relative importance, the bid-ask spread is more important than the number of daily CDS spreads statistically and economically. In the third chapter, I investigate the impact of the systematic risk on the volatility spread, i.e, the difference between the risk-neutral volatility and the physical volatility. I find that the systematic risk proportion of an underlying asset has a positive and significant impact on its volatility spread. The risk-neutral volatility in this study is measured with the increasingly popular approach known as the model-free risk-neutral volatility. The surprising positive systematic risk effect was first documented in Duan and Wei (2009) using the Black-Scholes implied volatility. I show that this effect is actually more prominent using the clearly better model-free risk-neutral volatility measure.

This thesis is a collection of three essays in empirical studies on derivatives. In the first chapter, I investigate whether credit default swap spreads are affected by how the total risk is decomposed into the systematic risk and the idiosyncratic risk for a given level of the total risk. The risk composition is measured by the systematic risk proportion, defined as the proportion of the systematic variance in the total variance. I find that a firm’s systematic risk proportion has a negative and significant effect on its CDS spreads. Moreover, this empirical finding is robust to various alternative specifications and estimations. Therefore, the composition of the total risk is an important determinant of CDS spreads. In the second chapter, I estimate the illiquidity premium in the CDS spreads based on Jarrow’s illiquidity-modified Merton model using the transformed-data maximum likelihood estimation method. I find that the average model implied CDS illiquidity premium is about 15 basis points, accounting for 12% of the average level of the CDS spread. I further investigate how this parameter is affected by CDS liquidity measures such as the percentage bid-ask spread and the number of daily CDS spreads available in one month. I find that both liquidity measures are significant determinants of the model implied CDS illiquidity premium. In terms of relative importance, the bid-ask spread is more important than the number of daily CDS spreads statistically and economically. In the third chapter, I investigate the impact of the systematic risk on the volatility spread, i.e, the difference between the risk-neutral volatility and the physical volatility. I find that the systematic risk proportion of an underlying asset has a positive and significant impact on its volatility spread. The risk-neutral volatility in this study is measured with the increasingly popular approach known as the model-free risk-neutral volatility. The surprising positive systematic risk effect was first documented in Duan and Wei (2009) using the Black-Scholes implied volatility. I show that this effect is actually more prominent using the clearly better model-free risk-neutral volatility measure.

Commercial mortgage underwriters have traditionally relied upon a standard set of criteria for approving and pricing loans. The increased level of commercial mortgage loan defaults from 1% at the start of 2009 to 9.32% by the end of 2011 provides motivation for questioning underwriting standards which previously served the lending industry well. This dissertation investigates factors that affect the probability of Non-performance among commercial mortgage-backed security (CMBS) loans, proposes conditions under which the standard ratios may not apply, and tests additional criteria which may prove useful during economic periods previously not experienced by commercial mortgage underwriters. In this dissertation, Cap Rate Spread, the difference between the cap rate of a property and the Coupon Rate of the associated loan, is introduced to test whether the probability of Non-performance can be better predicted than by relying on traditional commercial mortgage underwriting criteria such as Loan to Value (LTV) and Debt Service Coverage Ratio (DSCR). Testing the research hypotheses with a probit model using a database of 47,883 U.S. CMBS loans from 1993 to 2011, Cap Rate Spread is found to have a significantly negative relationship with loan Non-performance. That is, as the Cap Rate Spread falls, the probability of Non-performance rises appreciably. A numerical model suggests that among loans which would have passed the standard ratio tests requiring loans to have values of LTV less than .8 and DSCR greater than 1.25, a Cap Rate Spread criteria requiring loans to have a value greater than 1% would have prevented the origination of an additional 1,798 CMBS loans reducing the rate of Non-performance from 14.9% with only the LTV and DSCR criteria to just 11.6% by adding the Cap Rate Spread criteria. Of course, adding additional criteria will also lead to errors of rejecting loans which would have performed well. Back testing with the same sample of CMBS loans, this Type I error rate rises from 19% with only the LTV and DSCR criteria to 34% with the addition of the Cap Rate Spread. Ultimately, CMBS loan underwriters must individually determine an acceptable level of Non-performance appropriate to their business model and tolerance for risk. Using intuition, experience, tools, and rules, each underwriter must choose a balance between the competing risks of rejecting potentially profitable loans and accepting loans which will fail. This research result is important because it helps deepen our understanding of the relationships between property income and loan performance and provides an additional tool that underwriters may employ in assessing CMBS loan risk.

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