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 I also use it to examine new published and unpublished data, testing for (and finding) ratings path-dependency, and otherwise exploring the effect of ratings changes on different bond sectors.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?

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?

為了研究總體因子與產業違約率之間的關聯性, 本文以信用投資組合觀點模型(CPV) 做為開端, 建立在具評等基礎下的違約損失模型, 並以投機等級違約率估計出移轉係數矩陣, 進而模擬各產業條件移轉矩陣, 藉以反應在各種不同總體情境下, 產業內各評等的移轉機率及違約機率。此外, 本文亦建立不分評等的簡化違約損失模型, 並將兩模型做一比較。最後, 我們以台灣537 家上市櫃公司做為投資組合樣本, 分別模擬出兩模型的條件違約損失分配。進一步計算風險指標,以此做為未來規劃資本計提的基礎。最後結果顯示, 投資組合違約情況確實受總體因子影響, 且發現若投資組合中評等越差公司之曝險越小, 將有助於降低組合資產風險。

nÃo hà / Esta pesquisa objetiva o desenvolvimento de um modelo de risco para instituiÃÃes bancÃrias, fundamentado em Ãndices financeiros, com a aplicaÃÃo de conceitos de matrizes de migraÃÃo de ratings. Para isso, sÃo utilizados dados contÃbeis pÃblicos destas entidades, que recebem o acompanhamento de autoridades monetÃrias, devido ao risco sistÃmico que podem representar, e das matrizes de migraÃÃo de rating, que tÃm se tornado de grande utilidade na teoria moderna de administraÃÃo do risco. Assim, em uma abordagem teÃrica e experimental, foi gerado um modelo, com a utilizaÃÃo de matrizes de migraÃÃo, construÃdas a partir de classificaÃÃes de risco baseadas em Ãndices financeiros. Foram utilizados demonstrativos financeiros semestrais e anuais de 79 instituiÃÃes bancÃrias, no perÃodo de 2001 a 2009. Verificou-se que as matrizes de migraÃÃo que mais se aproximavam de matrizes de rating foram aquelas com menores nÃmeros de classes de risco e de maiores intervalos. Quanto aos Ãndices da equaÃÃo do modelo, verificou-se que a alavancagem e a relaÃÃo capital/depositantes foram os que apresentaram maiores ponderaÃÃes. Quando as notas estimadas foram comparadas com as notas das agÃncias Austin e Fitch, observou-se baixo nÃmero de notas iguais, porÃm em quantidade significativa, quando consideradas tambÃm as notas iguais e as que diferiam em apenas um nÃvel de risco. / This research aims to develop a risk model for banks, based on financial indices, with the application of concepts of migration matrices ratings. For this, public accounting data are used these entities that receive the monitoring of monetary authorities, due to the systemic risk that may represent, and rating migration matrices, which have become very useful in the modern theory of risk management. Thus, in a theoretical and experimental, a model was created with the use of migration matrices, constructed from risk scores based on financial indices. We used half-yearly and annual financial statements of 79 banks in the period 2001 to 2009. It was found that the matrix of migration that were closest to the rating matrices were those with smaller numbers of classes of risk and greater intervals. Regarding the indexes of the model equation, it was found that the leverage ratio and capital / depositors were those with higher weightings. When notes were compared with the estimated scores of agencies Fitch and Austin, we found low numbers of equal notes, but in significant amounts when the notes considered equal and the only one that differed in level of risk.

In order to be compliant with the Basel regulations, banks need to compute two probabilities of default (PDs): point-in-time (PIT) and through-the-cycle (TTC). The aim is to explain fluctuations in the rating system, which are expected to be affected by systematic and idiosyncratic factors. Being able to, in an objective manner, determine whether the rating system is taking the business cycle - i.e the systematic factors - into account when assigning a credit rating to an obligor is useful in order to evaluate PD-models. It is also necessary for banks in order to use their own risk parameters and models instead of standardized models, which is desirable for most banks as it could lower capital requirements. This thesis propose a new measure for the degree of PIT-ness. This measure aims to be especially useful when examining a low default portfolio. The proposed measure is built on a markovian approach of the credit rating system. In order to find a suitable measure for a low default portfolio, the proposed measure takes into account credit rating migrations, the seasonal component of the business cycle and time series analysis. An analysis were performed between two different credit portfolios in order to interpret results. The results demonstrated that the degree of PIT-ness was lower in a low default portfolio in comparison with a sampled portfolio which displayed a greater amount of rating migrations with a larger magnitude. The importance of considering relevant macroeconomic variables to represent the business cycle was mentioned amongst the most important factors to consider in order to receive reliable results given the proposed measure. / För att uppfylla Basel regelverken behöver banker beräkna två sannolikheter för fallissemang (PD): point-in-time (PIT) och through-the-cycle (TTC). Målet är att förklara fluktuationer i betygssystemet, som förväntas påverkas av systematiska och idiosynkratiska faktorer. Att på ett objektivt sätt kunna avgöra om betygssystemet tar hänsyn till affärscykeln - dvs de systematiska faktorerna - när man tilldelar en kredittagare ett kreditbetyg är användbart för att utvärdera PD-modeller. Detta är också nödvändigt för att banker ska få använda sina egna riskparametrar och modeller istället för standardiserade modeller, vilket är önskvärt för de flesta banker eftersom det kan sänka kapitalkraven. Denna avhandling föreslår ett nytt mått för att mäta graden av PIT-ness. Detta mått syftar till att vara särskilt användbart när man utvärderar en kreditportfölj med få fallissemang. Det föreslagna måttet är byggt på en Markov tillämpning på kreditbetygssystemet. För att hitta ett lämpligt mått för en kreditportfölj med få fallissemang, tar det föreslagna måttet hänsyn till kreditbetygsmigrationer, säsongskomponenten i affärscykeln och tidsserieanalys. En analys utfördes mellan två olika kreditportföljer för att tolka resultaten. Resultaten visade att graden av PIT-ness var lägre i en kreditportfölj med få fallissemang jämfört med en testportfölj som uppvisade en större mängd kreditbetygsmigrationer med en större magnitud. Vikten av att beakta relevanta makroekonomiska variabler för att representera affärscykeln nämndes bland de viktigaste faktorerna att beakta för att få tillförlitliga resultat givet det föreslagna måttet.