Is jump risk in iTraxx Sector Indices diversifiable?

The article presents an analysis of jump risks in iTraxx Europe index in a multivariate structural time-series setting for the stochastic process, as well as in the credit default swap (CDS) market. It also examines the rapid development of the credit derivatives market, particularly the CDS market. This analysis found a significant Poisson-distributed jumps in the iTraxx Non-Financials index and its subindices. Based on a statistical analysis, nondiversifiable jump risk strongly exists in the CDS market.

Oil price uncertainty and sovereign risk: evidence from Asian economies

In this paper, we test whether oil price uncertainty predicts credit default swap (CDS) returns for eight Asian countries. We use the Westerlund and Narayan, 2011 and Westerlund and Narayan, 2012 predictability test that accounts for any persistence in and endogeneity of the predictor variable. The estimator also accounts for any heteroskedasticity in the regression model. In-sample evidence reveals that oil price uncertainty predicts CDS returns for three Asian countries, whereas out-of-sample evidence suggests that oil price uncertainty predicts CDS returns for six countries.

Occupational light vehicle use: characterising the at-risk population

Previous occupational light vehicle research has concentrated on employees using cars. The aim of this study was to identify and characterise the total occupational light vehicle-user population and compare it with the privately-used light vehicle population. Occupational light vehicle and private light vehicle populations were identified through use-related 2003 registration categories from New South Wales Roads and Traffic Authority data. Key groups of occupational light vehicle registration variables were comparatively assessed as potential determinants of occupational light vehicleuser risks. These comparisons were expressed as odds ratios with 95% Confidence Intervals. The occupational light vehicle population vehicles (n=646,201) comprised 18% of all light vehicle registrations. A number of statistical differences emerge between the two populations. For instance, 86% of occupational light vehicle registrants were male versus 65% of private registrants, and 56% of the occupational users registered load shape vehicles versus 20% of the private registrants. Occupational light vehicles registered for farming or taxi use were more than six times more likely to belong to sole-traders than organisations. Sole-traders were nearly twice as likely to register light-trucks, and twice as likely to register older vehicles, than organisations. This study demonstrates that the occupational light vehicle user population is larger and more diverse than previously shown with characteristics likely to increase the relative risks of motor vehicle crashes. More occupational light vehicles were load shapes and therefore likely to have poorer crashworthiness ratings than cars. Occupational light vehicles are frequently used by sole-traders for activities with increased OHS risks including farming and taxi use. Further exploration of occupational light vehicle-user crash risks should include all vehicle types, work arrangements and small ‘fleets’.

Avaliação do risco de crédito: aplicação do modelo KMV para obter a probabilidade de default no setor siderúrgico

Credit risk management has assumed increasing importance for the managers and directors of enterprises. Thus, different approaches aimed to measure the probability of default are under discussion nowadays. This paper evaluates models that have become more popular over the last 30 years in order forecast defaults or to provide information regarding to financial difficulties of enterprises. This paper will focus on the KMV model in order to estimate the probability of default, its methodology based on market value of the asset and its volatility and finally estimate the probability of default. Finally, to test the KMV model will be used a sample of global steel companies that have credit in Companhia Vale do Rio Doce (CVRD), which will allow us to make comparisons with the models presented in this work.

Default mercado de crédito parcelado para bens duráveis : veículos automotores

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.

Estudo sobre o efeito de variáveis macro econômico e do spread de credit default swap no risco de evento de crédito soberano

Este trabalho explora a realização de default soberano em função da estrutura de spreads de CDS (Credit Default Swap). Pode-se dizer que os spreads revelam a probabilidade de default de um país. Aplicamos a metodologia proposta neste trabalho para Argentina, Coreia, Equador, Indonésia, México, Peru, Turquia, Ucrânia, Venezuela e Rússia. Nós mostramos que um modelo de um único fator seguindo um processo lognormal captura a probabilidade de default. Também mostramos que as variáveis macro econômicas inflação, desemprego e crescimento não explicam a variável dependente do estudo (probabilidade de default). Cada país reage de maneira diferente a crise econômica que a leva a não honrar seus compromissos com as dívidas contraídas.

Um estudo sobre a probabilidade de Default para bancos de médio e pequeno porte no Brasil

Esta dissertação tem por objetivo primário encontrar uma métrica de risco para bancos elegível a ser uma componente específica em futuros modelos de custo de capital. Como objetivo secundário, este trabalho descreve um processo de modelagem passível de ser estendido a outros segmentos bancários. O conjunto de contribuições deste trabalho consiste na visão de aplicação, no objeto de estudo (bancos de pequeno e médio porte com baixa diversificação de produtos ou segmentos no sistema financeiro brasileiro) e na acessibilidade do processo de modelagem estruturado

Endogenous borrowing constraints and default when markets are incomplete

Incomplete markets and non-default borrowing constraints increase the volatility of pricing kernels and are helpful when addressing assetpricing puzzles. However, ruling out default when markets are in complete is suboptimal. This paper endogenizes borrowing constraints as an intertemporal incentive structure to default. It modeIs an infinitehorizon economy, where agents are allowed not to pay their liabilities and face borrowing constraints that depend on the individual history of default. Those constraints trade off the economy's risk-sharing possibilities and incentives to prevent default. The equilibrium presents stationary properties, such as an invariant distribution for the assets' solvency rate.

Wrong-way risk in stock swaps : measuring counterparty credit risk and CVA

Uma forma interessante para uma companhia que pretende assumir uma posição comprada em suas próprias ações ou lançar futuramente um programa de recompra de ações, mas sem precisar dispor de caixa ou ter que contratar um empréstimo, ou então se protegendo de uma eventual alta no preço das ações, é através da contratação de um swap de ações. Neste swap, a companhia fica ativa na variação de sua própria ação enquanto paga uma taxa de juros pré ou pós-fixada. Contudo, este tipo de swap apresenta risco wrong-way, ou seja, existe uma dependência positiva entre a ação subjacente do swap e a probabilidade de default da companhia, o que precisa ser considerado por um banco ao precificar este tipo de swap. Neste trabalho propomos um modelo para incorporar a dependência entre probabilidades de default e a exposição à contraparte no cálculo do CVA para este tipo de swap. Utilizamos um processo de Cox para modelar o instante de ocorrência de default, dado que a intensidade estocástica de default segue um modelo do tipo CIR, e assumindo que o fator aleatório presente na ação subjacente e que o fator aleatório presente na intensidade de default são dados conjuntamente por uma distribuição normal padrão bivariada. Analisamos o impacto no CVA da incorporação do riscowrong-way para este tipo de swap com diferentes contrapartes, e para diferentes prazos de vencimento e níveis de correlação.

Spatial Distribution of Seropositive Dogs to Leptospira spp. and Evaluation of Leptospirosis Risk Factors Using a Decision Tree

Background: Leptospirosis is an important zoonotic disease associated with poor areas of urban settings of developing countries and early diagnosis and prompt treatment may prevent disease. Although rodents are reportedly considered the main reservoirs of leptospirosis, dogs may develop the disease, may become asymptomatic carriers and may be used as sentinels for disease epidemiology. The use of Geographical Information Systems (GIS) combined with spatial analysis techniques allows the mapping of the disease and the identification and assessment of health risk factors. Besides the use of GIS and spatial analysis, the technique of data mining, decision tree, can provide a great potential to find a pattern in the behavior of the variables that determine the occurrence of leptospirosis. The objective of the present study was to apply Geographical Information Systems and data prospection (decision tree) to evaluate the risk factors for canine leptospirosis in an area of Curitiba, PR.Materials, Methods & Results: The present study was performed on the Vila Pantanal, a urban poor community in the city of Curitiba. A total of 287 dog blood samples were randomly obtained house-by-house in a two-day sampling on January 2010. In addition, a questionnaire was applied to owners at the time of sampling. Geographical coordinates related to each household of tested dog were obtained using a Global Positioning System (GPS) for mapping the spatial distribution of reagent and non-reagent dogs to leptospirosis. For the decision tree, risk factors included results of microagglutination test (MAT) from the serum of dogs, previous disease on the household, contact with rats or other dogs, dog breed, outdoors access, feeding, trash around house or backyard, open sewer proximity and flooding. A total of 189 samples (about 2/3 of overall samples) were randomly selected for the training file and consequent decision rules. The remained 98 samples were used for the testing file. The seroprevalence showed a pattern of spatial distribution that involved all the Pantanal area, without agglomeration of reagent animals. In relation to data mining, from 189 samples used in decision tree, a total of 165 (87.3%) animal samples were correctly classified, generating a Kappa index of 0.413. A total of 154 out of 159 (96.8%) samples were considered non-reagent and were correctly classified and only 5/159 (3.2%) were wrongly identified. on the other hand, only 11 (36.7%) reagent samples were correctly classified, with 19 (63.3%) samples failing diagnosis.Discussion: The spatial distribution that involved all the Pantanal area showed that all the animals in the area are at risk of contamination by Leptospira spp. Although most samples had been classified correctly by the decision tree, a degree of difficulty of separability related to seropositive animals was observed, with only 36.7% of the samples classified correctly. This can occur due to the fact of seronegative animals number is superior to the number of seropositive ones, taking the differences in the pattern of variable behavior. The data mining helped to evaluate the most important risk factors for leptospirosis in an urban poor community of Curitiba. The variables selected by decision tree reflected the important factors about the existence of the disease (default of sewer, presence of rats and rubbish and dogs with free access to street). The analyses showed the multifactorial character of the epidemiology of canine leptospirosis.

Pricing in stochastic-local volatility models with default

In recent years is becoming increasingly important to handle credit risk. Credit risk is the risk associated with the possibility of bankruptcy. More precisely, if a derivative provides for a payment at cert time T but before that time the counterparty defaults, at maturity the payment cannot be effectively performed, so the owner of the contract loses it entirely or a part of it. It means that the payoff of the derivative, and consequently its price, depends on the underlying of the basic derivative and on the risk of bankruptcy of the counterparty. To value and to hedge credit risk in a consistent way, one needs to develop a quantitative model. We have studied analytical approximation formulas and numerical methods such as Monte Carlo method in order to calculate the price of a bond. We have illustrated how to obtain fast and accurate pricing approximations by expanding the drift and diffusion as a Taylor series and we have compared the second and third order approximation of the Bond and Call price with an accurate Monte Carlo simulation. We have analysed JDCEV model with constant or stochastic interest rate. We have provided numerical examples that illustrate the effectiveness and versatility of our methods. We have used Wolfram Mathematica and Matlab.