Thesis (Ph.D.)--University of Texas at Arlington, 2009.

The expected yield to maturity on a defaultable obligation equals the nominal yield less expected default losses. However, in a mark-to-market world, one doesn't have the luxury of reporting one's performance on the basis of yield to maturity. Total return is calculated for an arbitrary holding period, and must reflect any mark-to-market gains or losses as at the close of the period-gains or losses that can be triggered by the bond's upgrade or downgrade. Thus to estimate expected total return, one must estimate not only expected default losses, but also the impact on capital price of expected ratings transitions. This paper begins with the observation that a bond which is blessed by more favourable transition characteristics is likely to produce a higher total return, and poses the question of how that benefit can be quantified. How much is it worth? To answer the question, I start by specifying a formal bond-pricing model reflective of ratings transitions. I survey various statistical methods and past research efforts to identify the ratings-transition matrix which best parametrises the model, and propose a novel test for selecting between competing matrices. Using this approach, I replicate several important studies of ratings transitions. I also use it to examine new published and unpublished data, testing for (and finding) ratings path-dependency, and otherwise exploring the effect of ratings changes on different bond sectors. I then turn to the question of whether it is possible to estimate bond-specific transition probabilities, and propose a way to do so. I combine these efforts into the specifications for a pricing model capable of answering the question: How much is it worth?

Diss. Stockholm : Handelshögskolan, 2006.

Thesis (M. Phil.)--University of Hong Kong, 2008. / Includes bibliographical references (leaf 64-68) Also available in print.

Thesis (Ph. D.)--University of Texas at Austin, 2005. / Vita. Includes bibliographical references.

Η λειτουργία της διαχείρισης κινδύνων συγκεντρώνει ιδιαίτερο ενδιαφέρον και συνεχή μέριμνα από την πλευρά της Διοίκησης των χρηματοπιστωτικών ιδρυμάτων και αποτελεί μια από τις βασικότερες λειτουργίες του. Με γνώμονα τη διατήρηση της σταθερότητας στοχεύει σε μια διαρκή εξέλιξη αποτελεσματικού πλαισίου διαχείρισης κινδύνων για τη μείωση των ενδεχόμενων αρνητικών συνεπειών. Η δραστηριότητα και η κερδοφορία του χρηματοπιστωτικού ιδρύματος είναι συνυφασμένη με την ανάληψη πιστωτικού κινδύνου. Ο πιστωτικός κίνδυνος με τη σειρά του απορρέει από δύο πηγές και είναι συνυφασμένος με το ενδεχόμενο αδυναμίας των αντισυμβαλλόμενων να εκπληρώσουν τις υποχρεώσεις τους. Από τη μία πλευρά, είναι οι «πελάτες» της τράπεζας οι οποίοι δανείζονται και στη συνέχεια αδυνατούν να εκπληρώσουν τις υποχρεώσεις τους και από την άλλη πλευρά είναι το ίδιο το χρηματοπιστωτικό ίδρυμα το οποίο μπορεί να δανειστεί κεφάλαια (από την κεντρική ευρωπαϊκή τράπεζα ) είτε για να ενισχύσει την λειτουργία του είτε για να επιβιώσει και αδυνατεί στη συνέχεια να εκπληρώσει τις υποχρεώσεις του προς το δανειστή του. Στην παρούσα διπλωματική εργασία, αναλύεται και παρουσιάζεται ο πιστωτικό κίνδυνος και τα χαρακτηριστικά που τον συνθέτουν καθώς και οι πλέον σύγχρονες τεχνικές που ακολουθούνται στην αγορά για την αποτίμηση του. Στο πρώτο στάδιο γίνεται μια σύντομη και ουσιαστική ανάλυση του τραπεζικού συστήματος. Ουσιαστικά, παρουσιάζεται η δομή και η λειτουργία του χρηματοπιστωτικού συστήματος καθώς και οι υποκατηγορίες που τις αποτελούν όπως επίσης και οι μέθοδοι και τα εργαλεία που χρησιμοποιούνται για την αποτελεσματικότερη λειτουργία τους. Δεύτερο σκέλος της εργασίας αυτής αποτελεί το εποπτικό πλαίσιο το οποίο συσχετίζεται με την προληπτική εποπτεία των τραπεζών, στην μείωση των κινδύνων και στη διαφάνεια των συναλλαγών. Τα μέτρα και τα εργαλεία που χρησιμοποιούνται στο θεσμικό-ρυθμιστικό πλαίσιο έχουν αλλάξει σε βάθος χρόνου σύμφωνα με τις ανάγκες και την γενικότερη εικόνα του οικονομικού συστήματος. Στο τρίτο κεφάλαιο αναλύονται κάποιες γενικές κατηγορίες κινδύνων όπως ο πιστωτικός, ο λειτουργικός και ο κίνδυνος αγοράς. Στη συνέχεια, παρουσιάζεται ο τρόπος με τον οποίο ένα χρηματοπιστωτικό ίδρυμα καθορίζει τον αναμενόμενο κίνδυνο, δηλαδή το μέσο επίπεδο ζημιών από τα δάνεια που έχει χορηγήσει καθώς και τη μέθοδο κάλυψης των μη-αναμενόμενων ζημιών. Τα Credit Ratings, δηλαδή η κατάταξη των δανειοληπτών με βάση την πιθανότητα τους να αθετήσουν τις υποχρεώσεις τους αποτελεί σημαντικό μέρος της παρούσας εργασίας. Η ανάλυση εστιάζεται στην ερμηνεία των βαθμολογήσεων που δίνουν οι οίκοι αξιολόγησης στους δανειστές. Στη συνέχεια έγινε μια σύντομη ανάλυση των πιο γνωστών υποδειγμάτων μέτρησης του πιστωτικού κινδύνου ή ακόμα και πρόβλεψης πτώχευσης οικονομικών μονάδων (επιχειρήσεων ή τραπεζών) η οποία οφείλεται στον πιστωτικό κίνδυνο. Τα υποδείγματα αυτά κατηγοριοποιούνται σε δύο ομάδες αυτές των Παραδοσιακών Υποδειγμάτων και αυτές των Δομικών Υποδειγμάτων. Με βάση τη μορφή των υποδειγμάτων αυτών πραγματοποιείται η εμπειρική ανάλυση η οποία έχει διερευνητικό χαρακτήρα και απώτερος σκοπός της είναι να εξετάσει κατά πόσο επεξηγούν διάφοροι χρηματοοικονομικοί δείκτες την εξαρτημένη μεταβλητή μιας παλινδρόμησης, η οποία στην προκειμένη περίπτωση είναι οι βαθμολογήσεις της πιστοληπτικής ικανότητας χρηματοπιστωτικών ιδρυμάτων από τους οίκους αξιολόγησης σε βάθος χρόνου επτά ετών. / -

Loss given default (LGD) modelling has become increasingly important for banks as they are required to comply with the Basel Accords for their internal computations of economic capital. Banks and financial institutions are encouraged to develop separate models for different types of products. In this thesis we apply and improve several new algorithms including support vector machine (SVM) techniques and mixed effects models to predict LGD for both corporate bonds and retail loans. SVM techniques are known to be powerful for classification problems and have been successfully applied to credit scoring and rating business. We improve the support vector regression models by modifying the SVR model to account for heterogeneity of bond seniorities to increase the predictive accuracy of LGD. We find the proposed improved versions of support vector regression techniques outperform other methods significantly at the aggregated level, and the support vector regression methods demonstrate significantly better predictive abilities compared with the other statistical models at the segmented level. To further investigate the impacts of unobservable firm heterogeneity on modelling recovery rates of corporate bonds a mixed effects model is considered, and we find that an obligor-varying linear factor model presents significant improvements in explaining the variations of recovery rates with a remarkably high intra-class correlation being observed. Our study emphasizes that the inclusion of an obligor-varying random effect term has effectively explained the unobservable firm level information shared by instruments of the same issuer. At last we incorporate the SVM techniques into a two-stage modelling framework to predict recovery rates of credit cards. The two-stage model with a support vector machine classifier is found to be advantageous on an out-of-time sample compared with other methods, suggesting that an SVM model is preferred to a logistic regression at the classification stage. We suggest that the choice of regression models is less influential in prediction of recovery rates than the choice of classification methods in the first step of two-stage models based on the empirical evidence. The risk weighted assets of financial institutions are determined by the estimates of LGD together with PD and EAD. A robust and accurate LGD model impacts banks when making business decisions including setting credit risk strategies and pricing credit products. The regulatory capital determined by the expected and unexpected losses is also important to the financial market stability which should be carefully examined by the regulators. In summary this research highlights the importance of LGD models and provides a new perspective for practitioners and regulators to manage credit risk quantitatively.

O mercado de crédito de longo prazo, abordado aqui através dos contratos de debênture, vem se fortalecendo no Brasil após o início do Plano Real, onde a estabilização da economia permitiu que suas cláusulas contratuais migrassem para o controle de risco relativo à firma frente a anterior preocupação com o ambiente econômico conturbado, conforme exposto em Silva e Leal (2008). Assim, este trabalho tenta prever a variável Distante to Default (DD) apresentada em Crosbie e Bohn (2003) através da estrutura proposta por Collin-Dufresne e Goldstein (2001). Para o quartil mais líquido da amostra, o erro percentual médio (EPM) para um horizonte de previsão de cinco anos é de 52%, e de 21% quando considerada a previsão perfeita da volatilidade. O EPM mostra-se muito sensível à liquidez das empresas em bolsa. / The long-term credit market, addressed here through debenture contracts, has gained strength in Brazil after the start of the Real Plan, where stabilization of the economy has allowed its contractual covenants migrate to the firm's risk control in spite of the previous troubled economic environment, outlined in Silva e Leal (2008). Then, this work tries to forecast the Distance to Default variable (DD) from Crosbie e Bohn (2003) through the proposed structure by Collin- Dufresne e Goldstein (2001). For the sample's most liquid quartile, the mean percentage error (MPE) for a forecast horizon of five years is 52%, and 21% when considering perfect volatility forecast. The MPE is very sensitive to firm's market liquidity.

Master of Agribusiness / Department of Agricultural Economics / Allen M. Featherstone / Cash management practices for corporate treasurers are in a state of instability in recent years. Events during the credit crisis of 2008 have had an impact on how organization’s cash positions are managed. This has led corporate treasurers to juggle unprecedented amounts of cash across multiple bank counterparties and invest these funds based on previous investment policies with potentially inflexible limits. Many regulations have been passed to strengthen domestic and global financial systems, yet the risk of default is not completely removed and there are many uncertain ties that corporates face. To succeed in the uncertain financial environment, counterparty risk tools must be put in place to improve the visibility of potential operational risk, along with a higher frequency of reviewing and updating investment policies. It is crucial for corporates to look beyond the traditional market perceptions and bank credit ratings to evaluate counterparty risk. Although these continue to be a valuable metric, they should be incorporated with other forward looking market risk metrics such as credit default swaps, capital and asset resiliency metrics, and growth and profitability metrics to their current investment guidelines review. By integrating risk metrics to help formulate an investment policy, corporates can adapt to the changing financial environment. This thesis examined methodologies to develop a more accurate and immediate viewpoint of counterparty creditworthiness. This was done through the creation of models using market information to set values to view the strength of counterparties and the likelihood of default. Models were created for both financial institutions and countries where cash or investments are placed. Depending on the models, this restricts the permissible investment options that an institution or country has. This approach allows the company to invest more with higher rated counterparties, and sets a maximum to those who are deemed high risk of default. The findings of this thesis identified that it is crucial to classify the right metrics and look beyond traditional market perceptions and bank credit ratings. By implementing a balanced process that regularly monitors current market indicators of counterparty risk, an organization will be in a stronger position to define and determine the potential risk. This creates a balanced view of both backward looking and forward looking metrics such as long term debt ratings and credit default swaps. These metrics were useful indicators of a counterparty’s strength. Because of the wide range of information available and cost, it went beyond the resources of the company to perform detailed ongoing analysis. It was also identified that a risk-adjusted approach to setting counterparty limits is crucial for managing counterparty exposure and the risk of default. To optimize liquidity, it is in the company’s best interest to place higher balances in institutions with the lowest risk of default. Grouping banks into tiers and assigning a percentage of total balance to each tier allows for financial institutions to have a specific limit capacity. Incorporating these tools on a frequent basis allows for real-time analysis of counterparty exposure and risk.

O mercado de crédito de longo prazo, abordado aqui através dos contratos de debênture, vem se fortalecendo no Brasil após o início do Plano Real, onde a estabilização da economia permitiu que suas cláusulas contratuais migrassem para o controle de risco relativo à firma frente a anterior preocupação com o ambiente econômico conturbado, conforme exposto em Silva e Leal (2008). Assim, este trabalho tenta prever a variável Distante to Default (DD) apresentada em Crosbie e Bohn (2003) através da estrutura proposta por Collin-Dufresne e Goldstein (2001). Para o quartil mais líquido da amostra, o erro percentual médio (EPM) para um horizonte de previsão de cinco anos é de 52%, e de 21% quando considerada a previsão perfeita da volatilidade. O EPM mostra-se muito sensível à liquidez das empresas em bolsa. / The long-term credit market, addressed here through debenture contracts, has gained strength in Brazil after the start of the Real Plan, where stabilization of the economy has allowed its contractual covenants migrate to the firm's risk control in spite of the previous troubled economic environment, outlined in Silva e Leal (2008). Then, this work tries to forecast the Distance to Default variable (DD) from Crosbie e Bohn (2003) through the proposed structure by Collin- Dufresne e Goldstein (2001). For the sample's most liquid quartile, the mean percentage error (MPE) for a forecast horizon of five years is 52%, and 21% when considering perfect volatility forecast. The MPE is very sensitive to firm's market liquidity.