Στη παρούσα μελέτη, αρχικά παρουσιάζονται από θεωρητική πλευρά θέματα που αφορούν το ρυθμιστικό πλαίσιο, τον πιστωτικό κίνδυνο, τα μη εξυπηρετούμενα δάνεια και οι έννοιες Ευρωζώνη και Ευρωσύστημα. Ακολούθως, με τη χρήση ενός οικονομετρικού μοντέλου επιχειρήθηκε ο προσδιορισμός των παραγόντων εκείνων που επηρεάζουν τον δείκτη μη εξυπηρετούμενων δανείων στην Ευρωζώνη. Ο δείκτης των μη εξυπηρετούμενων δανείων ουσιαστικά συνιστάται ως προσεγγιστική μεταβλητή του πιστωτικού κινδύνου και την περίοδο αυτή της παρατεταμένης ύφεσης αποτελεί ενδεχομένως τη μεγαλύτερη απειλή που αντιμετωπίζουν τα διάφορα τραπεζικά συστήματα όλου του κόσμου. Χρησιμοποιώντας συγκεντρωτικά δεδομένα (aggregate data) σε ένα πάνελ 13 χωρών της Ευρωζώνης για την περίοδο 2000-2008 και με την βοήθεια της fixed effect προσέγγισης, εντοπίστηκαν ισχυρές συσχετίσεις μεταξύ του NPL και διαφόρων μακροοικονομικών και τραπεζικών (banκ specific) παραγόντων. Πιο συγκεκριμένα, τα ευρήματα της εμπειρικής διερεύνησης, επιβεβαιώνουν τη διεθνή βιβλιογραφία καθώς από πλευράς τραπεζικών μεταβλητών ισχυρή επίδραση στο δείκτη μη εξυπηρετούμενων δάνειων εμφανίζει ο δείκτης κεφαλαιακής επάρκειας, ο δείκτης δάνεια προς καταθέσεις και ο δείκτης των μη εξυπηρετούμενων της προηγούμενης χρονιάς. Τέλος, από μακροοικονομικής πλευράς το δημόσιο χρέος και η ανεργία φαίνεται να είναι δυο επιπλέον παράγοντες που επιδρούν στη διαμόρφωση του δείκτη, αποτυπώνοντας ότι η κατάσταση της οικονομίας των χωρών της ευρωζώνης συνδέεται άρρηκτα με τον δείκτη NPL. / In this study, from the theoretical point of you, issues regarding regulation, credit risk, non-performing loans, Eurozone and Eurosystem are presented. Then, implementing an econometric model it was examined which factors influence the ratio of nonperforming loans in the Eurozone. It is worthwhile to mention that the ratio of NPLs can be used as a proxy of credit risk. Nowadays, credit risk seems to be the greatest risk, which banking systems are facing all over the world. Particularly, Using aggregate data on a panel of 13 countries for the period 2000-2008 and applying the fixed effect approach, strong correlations between the NPL and various macroeconomic and bank specific factors are confirmed. Our findings largely agree with the literature as, in terms of bank-specific variables, the capital ratio, the loans to deposits ratio and the rate of non-performing loans of the previous year appear to exert a powerful influence on the non-performing loans rate. At the same time, from a macroeconomic perspective, the public debt and unemployment seem to be two additional factors that affect the index, revealing that the state of the economy of Eurozone countries is clearly linked to the NPL index.

When banks lend capital to counterparties they take on a risk, known as credit risk which traditionally has been the largest risk exposure for banks. To be protected against potential default losses when lending capital, banks must hold a regulatory capital that is based on a regulatory formula for calculating risk weighted assets (RWA). This formula is part of the Basel Accords and it is implemented in the legal system of all European Union member states. The key parameters of the RWA formula are probability of default, loss given default and asset correlation. Banks today have the option to estimate the probability of default and loss given default by internal models however the asset correlation must be determined by a formula provided by the legal framework. This project is a first approach for Handelsbanken to study what would happen if banks were allowed to estimate asset correlation by internal models. We assess two models for estimating the asset correlation of a portfolio of Small and Medium Enterprices (SME). The estimates are compared with the asset correlation given by the regulatory formula and with estimates for another parameter called default correlation. The models are validated using predicted historical data and Monte-Carlo Simulations. For the studied SME portfolio, the models give similar estimates for the asset correlations and the estimates are lower than those given by the regulatory formula. This would imply a lower capital requirement if banks were allowed to use internal models to estimate the asset correlation used in the RWA formula. Default correlation, if not used synonymously with asset correlation, is shown to be another measure and should not be used in the RWA formula. / När banker lånar ut kapital till motparter tar de en risk, mer känt som kreditrisk som traditionellt har varit den största risken för banker. För att skydda sig mot potentiella förluster vid utlåning måste banker ha ett reglerat kapital som bygger på en formel för beräkning av riskvägda tillgångar (RWA). Denna formel ingår i Basels regelverk och är implementerad i rättssystemet i alla EU-länder. De viktigaste parametrarna för RWA-formeln är sannolikheten att fallera, förlustgivet fallissemang och tillgångskorrelation. Bankerna har idag möjlighet att beräkna de två variablerna sannolikheten att fallera och förlustgivet fallissemang med interna modeller men tillgångskorrelation måste bestämmas med hjälp av en standardformel givet från regelverket. Detta projekt är ett första tillvägagångssätt för Handelsbanken att studera vad som skulle hända om banker fick beräkna tillgångskorrelation med interna modeller. Vi analyserar två modeller för att skatta tillgångskorrelation i en portfölj av Små och Medelstora Företag (SME). Uppskattningarna jämförs sedan med den tillgångskorrelation som ges av regelverket och jämförs även mot en parameter som kallas fallissemangskorrelation. Modellerna som används för att beräkna korrelationerna valideras med hjälp av estimerat data och Monte-Carlo Simuleringar. För den studerade SME portföljen ges liknande uppskattningar för de båda tillgångskorrelationsmodellerna, samt visar det sig att de är lägre än den korrelationen som ges av regelverket. Detta skulle innebära ett lägre kapitalkrav om bankerna fick använda sig av interna modeller för att estimera tillgångskorrelation som används i RWA-formeln. Om fallissemangskorrelation inte används synonymt till tillgångskorrelation, visar det sig att fallisemangskorrelation är en annan mätning än tillgångskorrelation och bör inte användas i RWA-formeln.

Readjusting Historical Credit Ratings using Ordered Logistic Re-gression and Principal Component Analysis The introduction of the Basel II Accord as a regulatory document for creditrisk presented new concepts of credit risk management and credit risk mea-surements, such as enabling international banks to use internal estimates ofprobability of default (PD), exposure at default (EAD) and loss given default(LGD). These three measurements is the foundation of the regulatory capitalcalculations and are all in turn based on the bank’s internal credit ratings. Ithas hence been of increasing importance to build sound credit rating modelsthat possess the capability to provide accurate measurements of the credit riskof borrowers. These statistical models are usually based on empirical data andthe goodness-of-fit of the model is mainly depending on the quality and sta-tistical significance of the data. Therefore, one of the most important aspectsof credit rating modeling is to have a sufficient number of observations to bestatistically reliable, making the success of a rating model heavily dependenton the data collection and development state.The main purpose of this project is to, in a simple but efficient way, createa longer time series of homogeneous data by readjusting the historical creditrating data of one of Svenska Handelsbanken AB’s credit portfolios. Thisreadjustment is done by developing ordered logistic regression models thatare using independent variables consisting of macro economic data in separateways. One model uses macro economic variables compiled into principal com-ponents, generated through a Principal Component Analysis while all othermodels uses the same macro economic variables separately in different com-binations. The models will be tested to evaluate their ability to readjust theportfolio as well as their predictive capabilities. / Justering av historiska kreditbetyg med hjälp av ordinal logistiskregression och principialkomponentsanalys När Basel II implementerades introducerades även nya riktlinjer för finan-siella instituts riskhantering och beräkning av kreditrisk, så som möjlighetenför banker att använda interna beräkningar av Probability of Default (PD),Exposure at Default (EAD) och Loss Given Default (LGD), som tillsammansgrundar sig i varje låntagares sannoliket för fallissemang. Dessa tre mått ut-gör grunden för beräkningen av de kapitaltäckningskrav som banker förväntasuppfylla och baseras i sin tur på bankernas interna kreditratingsystem. Detär därmed av stor vikt för banker att bygga stabila kreditratingmodeller medkapacitet att generera pålitliga beräkningar av motparternas kreditrisk. Dessamodeller är vanligtvis baserade på empirisk data och modellens goodness-of-fit,eller passning till datat, beror till stor del på kvalitén och den statistiska sig-nifikansen hos det data som står till förfogande. Därför är en av de viktigasteaspekterna för kreditratingsmodeller att ha tillräckligt många observationeratt träna modellen på, vilket gör modellens utvecklingsskede samt mängdendata avgörande för modellens framgång.Huvudsyftet med detta projekt är att, på ett enkelt och effektivt sätt, skapaen längre, homogen tidsserie genom att justera historisk kreditratingdata i enportfölj med företagslån tillhandahållen av Svenska Handelsbanken AB. Jus-teringen görs genom att utveckla olika ordinala logistiska regressionsmodellermed beroende variabler bestående av makroekonomiska variabler, på olikasätt. En av modellerna använder makroekonomiska variabler i form av princi-palkomponenter skapade med hjälp av en principialkomponentsanalys, medande andra modelelrna använder de makroekonomiska variablerna enskilt i olikakombinationer. Modellerna testas för att utvärdera både deras förmåga attjustera portföljens historiska kreditratings samt för att göra prediktioner.

Counterparty Credit Risk and Interest Rate Derivatives Pricing Jakub Černý Abstract: This thesis deals with the pricing of OTC financial derivatives including the coun- terparty credit risk (CCR). It focuses on the interest rate derivatives for which the interest rate must be modeled as random. This is where they differ from the pricing of other derivatives. The credit valuation adjustment (CVA) concept is used to calculate CCR which is in line with current banking regulation Basel III. When we assume the independence of the underlying asset and the credit quality of the counterparty, we obtain an analytical expression of CVA. However, if the independence is violated, the CVA calculation becomes quite complicated. Specifically, the CVA of the inter- est rate swap (IRS) is calculated mainly using the simulation approach which is time and computationally consuming. Therefore, we bring two new methods for IRS CVA calculation where the CVA is expressed in a semi-analytical form. These methods use copula functions, particularly the Gaussian copula and the upper Fréchet bound, and we compare them numerically with a complex simulation study. Furthermore, we pro- pose a method of calibration of the correlation coefficient and we determine the impact of changes in the intensity of default on the final CVA with four...

Submitted by Marcia Bacha (marcia.bacha@fgv.br) on 2012-05-10T13:35:50Z No. of bitstreams: 1 343o FGV - Gustavo Ribas).pdf: 1032541 bytes, checksum: d5326372e73d2653dad404e2e9fc68a0 (MD5) / Approved for entry into archive by Marcia Bacha (marcia.bacha@fgv.br) on 2012-05-10T13:36:31Z (GMT) No. of bitstreams: 1 343o FGV - Gustavo Ribas).pdf: 1032541 bytes, checksum: d5326372e73d2653dad404e2e9fc68a0 (MD5) / Made available in DSpace on 2012-05-10T13:36:38Z (GMT). No. of bitstreams: 1 343o FGV - Gustavo Ribas).pdf: 1032541 bytes, checksum: d5326372e73d2653dad404e2e9fc68a0 (MD5) Previous issue date: 2011 / This paper aims to analyze the results of an operation to hedge a diversified credit portfolio through the use of equity. Initially, a reference to the main theoretical aspects of this dissertation with their definitions and literature review will be made. Furthermore, there will be an explanation about the basic parameters of the selection of the sample used and the period during which such protection strategy will be implemented. / Este trabalho tem como objetivo analisar os resultados de uma operação de hedge de um diversificado portfólio de crédito de empresas brasileiras através do uso de ativos de equity. Inicialmente, faz-se uma alusão aos principais aspectos teóricos da presente dissertação com suas definições e revisão bibliográfica. Posteriormente, são apresentados os parâmetros básicos da seleção da amostra utilizada e do período durante o qual tal estratégia de proteção será implementada.

Submitted by Marcos Vinícius Alvarenga Ramos da Silva (marcosvarsilva@gmail.com) on 2015-08-19T01:38:31Z No. of bitstreams: 1 Tese_V11.pdf: 1831740 bytes, checksum: ea23632eaf2595347fb5bf42e94cf418 (MD5) / Approved for entry into archive by Renata de Souza Nascimento (renata.souza@fgv.br) on 2015-08-19T15:50:35Z (GMT) No. of bitstreams: 1 Tese_V11.pdf: 1831740 bytes, checksum: ea23632eaf2595347fb5bf42e94cf418 (MD5) / Made available in DSpace on 2015-08-19T16:21:04Z (GMT). No. of bitstreams: 1 Tese_V11.pdf: 1831740 bytes, checksum: ea23632eaf2595347fb5bf42e94cf418 (MD5) Previous issue date: 2015-08-11 / Neste trabalho será apresentada a modelagem por regressão logística, com a finalidade de prever qual seria a inadimplência dos clientes que compõem o portfólio de uma grande instituição financeira do país. Sendo assim, será explorada a ideia de usar o conceito de provisionamento pura e simplesmente, através da estimação de uma probabilidade de default dado por um ou mais modelos estatísticos que serão construídos no decorrer do trabalho, conforme incentiva o comitê de Basileia. Um dos modelos será feito a partir de uma separação prévia de público através de clusters e a outra técnica a ser explorada será a criação de um modelo sem nenhuma separação. O objetivo será a comparação entre as duas métricas de classificação de risco e verificar os trade-off entre elas e os impactos de variáveis macroeconômicas nestes modelos. / This work presents the modeling logistic regression, in order to predict what the default of customers that make up the portfolio of a major financial institution in the country. Thus, the idea is exploited to use the concept of provisioning pure and simply, by estimating a probability of default data for one or more statistical models to be constructed during this work, as encourages Basel committee. One of the models will be done from a previous separation of the public through clusters and other technique being explored is the creation of a model with no separation. The goal will be to compare the two risk rating metrics and check the trade-off between them and the impacts of macroeconomic variables in these models.

Submitted by Renata Junqueira (repajunqueira@hotmail.com) on 2016-09-12T19:57:23Z No. of bitstreams: 1 Dissertação - Renata de Andrade Junqueira Ribeiro.pdf: 1064886 bytes, checksum: baad34290f965fc38c8c027553d693be (MD5) / Approved for entry into archive by GILSON ROCHA MIRANDA (gilson.miranda@fgv.br) on 2016-09-21T14:11:27Z (GMT) No. of bitstreams: 1 Dissertação - Renata de Andrade Junqueira Ribeiro.pdf: 1064886 bytes, checksum: baad34290f965fc38c8c027553d693be (MD5) / Approved for entry into archive by Marcia Bacha (marcia.bacha@fgv.br) on 2016-09-23T17:12:07Z (GMT) No. of bitstreams: 1 Dissertação - Renata de Andrade Junqueira Ribeiro.pdf: 1064886 bytes, checksum: baad34290f965fc38c8c027553d693be (MD5) / Made available in DSpace on 2016-09-23T17:12:24Z (GMT). No. of bitstreams: 1 Dissertação - Renata de Andrade Junqueira Ribeiro.pdf: 1064886 bytes, checksum: baad34290f965fc38c8c027553d693be (MD5) Previous issue date: 2016-08-29 / This paper uses an econometric model and identifies the relation between the perception of mining company Vale S.A.’s credit risk, measured by Credit Default Swap (CDS), and earnings surprises, measured by the difference between reported earnings per share (EPS) and EPS expected by market analysts. Conclusion is that a surprise in earning announcement significantly impacts Vale’s CDS and negative surprises tend to have higher influence than positive ones. Results suggest caution upon announcing future goals, since maintaining market expectations at reasonable levels could prevent sudden increases in funding costs. / Neste trabalho, é utilizado um modelo econométrico reduzido a fim de identificar a relação entre a percepção de risco de crédito da empresa mineradora Vale S.A., medida pelo Credit Default Swap (CDS), e a surpresa na divulgação de resultado, medida pela diferença entre o lucro por ação divulgado e o esperado pelos analistas de mercado. Conclui-se que uma surpresa no anúncio do resultado influencia significativamente o CDS da Vale e as surpresas negativas têm influência maior que as positivas. Os resultados sugerem cautela no anúncio de metas futuras, uma vez que a manutenção das expectativas de mercado em patamares moderados ajuda a evitar aumentos súbitos no custo de captação.

Submitted by Eduardo Toledo (dudutol@hotmail.com) on 2016-09-15T14:15:58Z No. of bitstreams: 1 Dissertação Eduardo Rietmann Toledo - Final.pdf: 4612894 bytes, checksum: ab143894eec8b23502f2222a0b9a5a27 (MD5) / Approved for entry into archive by GILSON ROCHA MIRANDA (gilson.miranda@fgv.br) on 2016-09-21T14:12:18Z (GMT) No. of bitstreams: 1 Dissertação Eduardo Rietmann Toledo - Final.pdf: 4612894 bytes, checksum: ab143894eec8b23502f2222a0b9a5a27 (MD5) / Approved for entry into archive by Marcia Bacha (marcia.bacha@fgv.br) on 2016-09-23T12:48:52Z (GMT) No. of bitstreams: 1 Dissertação Eduardo Rietmann Toledo - Final.pdf: 4612894 bytes, checksum: ab143894eec8b23502f2222a0b9a5a27 (MD5) / Made available in DSpace on 2016-09-23T12:49:08Z (GMT). No. of bitstreams: 1 Dissertação Eduardo Rietmann Toledo - Final.pdf: 4612894 bytes, checksum: ab143894eec8b23502f2222a0b9a5a27 (MD5) Previous issue date: 2016-05-31 / The aim of this study is to assess the impact of credit risk in the Brazilian stock cross-section return, and evaluate if a strategy based on this feature is able to generate positive and significant alpha. To measure credit risk, credit ratings were used assigned to Brazilian companies by the american agency Standard and Poors in the period between 2009 and 2014. First we divided ali firms in portfolios according to their credit risk and after we analyzed monthly returns of their stocks. Empirically, we find an evidence that the credit risk has a positive correlation in stock returns. However, as the strategy to operate based on credit risk was not able to generate significant alpha, it was not possible to statistically validate this effect on return. / O objetivo deste estudo é verificar o impacto do risco de crédito no retorno cross-section acionário brasileiro e avaliar se uma estratégia baseada nesta característica é capaz de gerar alfa positivo e significativo. Para mensurar o risco de crédito, foram utilizadas as notas de crédito atribuídas às empresas brasileiras pela agência americana Standard and Poors no período entre 2009 e 2014. Dividimos as empresas em portfolios de acordo com seu risco de crédito e analisamos os retornos mensais de suas ações. Empiricamente, encontramos indícios que o risco de crédito possui uma correlação positiva com o retorno acionário. No entanto, como a estratégia para operar baseada no risco de crédito não foi capaz de gerar alfa significativo, não foi possível validar estatisticamente este efeito sobre o retorno.

Made available in DSpace on 2010-04-20T21:00:29Z (GMT). No. of bitstreams: 3 rafaeljaborturma2004.pdf.jpg: 19565 bytes, checksum: 9fe13b15114451331e5e388307029987 (MD5) rafaeljaborturma2004.pdf: 532170 bytes, checksum: f71a18ba0313ae39ac8042e4a25ddee5 (MD5) rafaeljaborturma2004.pdf.txt: 171629 bytes, checksum: 405d0b510adacc24a36ff9e9e7806f82 (MD5) Previous issue date: 2007-01-18T00:00:00Z / This work is about the main issues of active credit portfolio management in commercial banks, which are abandoning the more traditional approach of credit management in favor of this new one. First, the paper presents a definition of active credit portfolio management, compares it with the traditional management and points out some reasons that led to the newer approach. Then, it adapts to credit portfolios the main concepts of Modern Portfolio Theory and presents some models on important data requirements for credit risk measurements like default probabilities, credit assets correlation and portfolio credit risk. It also presents the concepts of economic capital and Risk-Adjusted Return on Capital (RAROC) relatively to credit risk. This working paper discusses the active credit portfolio management functions and responsibilities and as a contribution presents, in light of this work’s considerations, a hypothetical structure of a credit department in a commercial bank which adopts active credit portfolio management. / Trata dos principais aspectos da administração ativa de portfólio de crédito a pessoa jurídica por bancos comerciais, que vem tomando o lugar do modo tradicional de administrar crédito. Inicialmente, apresenta a definição de administração ativa de portfólio de crédito, compara com a abordagem tradicional e aponta as motivações para o surgimento desta nova abordagem. Segue demonstrando as adaptações dos conceitos da Teoria Moderna de Portfólios aos portfólios de crédito e apresenta alguns modelos para a determinação de variáveis importantes para a mensuração do risco de crédito, tais como probabilidades de inadimplência, correlações entre ativos de crédito e risco de crédito de portfólio. Apresenta, ainda, o conceito de capital econômico e o Risk-Adjusted Return on Capital (RAROC) relativamente ao risco de crédito. Discute as responsabilidades e funções a serem desempenhadas pela administração ativa de portfólio de crédito e, como contribuição, apresenta, à luz das considerações deste trabalho, uma estrutura hipotética de um banco comercial que adota a administração ativa de portfólio de crédito.

Submitted by Roberta Lorenzon (roberta.lorenzon@fgv.br) on 2011-05-30T14:26:15Z No. of bitstreams: 1 63080100015.pdf: 781749 bytes, checksum: 32dd660d87d63789ab4a0ee0600ce50d (MD5) / Approved for entry into archive by Gisele Isaura Hannickel(gisele.hannickel@fgv.br) on 2011-05-30T14:47:36Z (GMT) No. of bitstreams: 1 63080100015.pdf: 781749 bytes, checksum: 32dd660d87d63789ab4a0ee0600ce50d (MD5) / Approved for entry into archive by Gisele Isaura Hannickel(gisele.hannickel@fgv.br) on 2011-05-30T14:48:59Z (GMT) No. of bitstreams: 1 63080100015.pdf: 781749 bytes, checksum: 32dd660d87d63789ab4a0ee0600ce50d (MD5) / Made available in DSpace on 2011-05-31T15:39:00Z (GMT). No. of bitstreams: 1 63080100015.pdf: 781749 bytes, checksum: 32dd660d87d63789ab4a0ee0600ce50d (MD5) Previous issue date: 2010-05-28 / The present work aims to study the macroeconomic factors influence in credit risk for installment autoloans operations. The study is based on 4.887 credit operations surveyed in the Credit Risk Information System (SCR) hold by the Brazilian Central Bank. Using Survival Analysis applied to interval censured data, we achieved a model to estimate the hazard function and we propose a method for calculating the probability of default in a twelve month period. Our results indicate a strong time dependence for the hazard function by a polynomial approximation in all estimated models. The model with the best Akaike Information Criteria estimate a positive effect of 0,07% for males over de basic hazard function, and 0,011% for the increasing of ten base points on the operation annual interest rate, toward, for each R$ 1.000,00 on the installment, the hazard function suffer a negative effect of 0,28% , and an estimated elevation of 0,0069% for the same amount added to operation contracted value. For de macroeconomics factors, we find statistically significant effects for the unemployment rate (-0,12%) , for the one lag of the unemployment rate (0,12%), for the first difference of the industrial product index(-0,008%), for one lag of inflation rate (-0,13%) and for the exchange rate (-0,23%). We do not find statistic significant results for all other tested variables. / The present work aims to study the macroeconomic factors influence in credit risk for installment autoloans operations. The study is based on 4.887 credit operations surveyed in the Credit Risk Information System (SCR) hold by the Brazilian Central Bank. Using Survival Analysis applied to interval censured data, we achieved a model to estimate the hazard function and we propose a method for calculating the probability of default in a twelve month period. Our results indicate a strong time dependence for the hazard function by a polynomial approximation in all estimated models. The model with the best Akaike Information Criteria estimate a positive effect of 0,07% for males over de basic hazard function, and 0,011% for the increasing of ten base points on the operation annual interest rate, toward, for each R$ 1.000,00 on the installment, the hazard function suffer a negative effect of 0,28% , and an estimated elevation of 0,0069% for the same amount added to operation contracted value. For de macroeconomics factors, we find statistically significant effects for the unemployment rate (-0,12%) , for the one lag of the unemployment rate (0,12%), for the first difference of the industrial product index(-0,008%), for one lag of inflation rate (-0,13%) and for the exchange rate (-0,23%). We do not find statistic significant results for all other tested variables.