| Name: | Description: | Size: | Format: | |
|---|---|---|---|---|
| 1.51 MB | Adobe PDF |
Abstract(s)
O risco de crédito e a sua mensuração são o principal foco de uma instituição de crédito, facto em muito despoletado pela crise financeira atual, que trouxe consigo restrições de crédito, fruto da menor liquidez dos mercados financeiros mundiais e acrescido do elevado número de incumprimentos verificados, tanto pelas pessoas coletivas como singulares. Este elevado incumprimento advém, entre muitos outros fatores, da má medição de risco de crédito que se traduz no financiamento de devedores com elevadas probabilidades de incumprir as suas obrigações.
Este trabalho incide na medição da probabilidade de incumprimento de pessoas singulares. Foi assim estimado um modelo econométrico para determinar uma notação de risco de crédito, partindo de dados do Inquérito à Situação Financeira das Famílias realizado em 2010, em Portugal. Foi possível não só determinar a probabilidade de incumprimento de uma família, como também determinar a exposição a incumprimento e a perda em caso de incumprimento.
O modelo proposto teve como base uma regressão probabilística objeto de calibração, com base na junção de variáveis explicativas já estudadas por outros autores. Para confirmar a solidez do modelo realizou-se uma análise estatística, de precisão, ajuste e respetiva validação do mesmo.
Concluiu-se que das variáveis explicativas incluídas no modelo, o número de crianças, a recusa de crédito e a deterioração das condições contribuem de forma significativa e positiva para a probabilidade de incumprir. Por outro lado, a propriedade de habitação contribui para a diminuição da probabilidade de incumprimento de um agregado familiar.
Credit risk and its measurement are the primary focus of a credit institution, especially since the start of the current financial crisis, which has brought credit constraints to the illiquidity of markets and a large number of defaults observed for firms and individuals. This failure arises from poor measurement of credit risk which translates in financing borrowers with high probabilities of default. This dissertation focuses on the measurement of the household probability of default. We estimate an econometric model to determine a credit rating, based on the data from the Household Finance and Consumption Survey held in 2010, in Portugal. It was possible not only to determine the household probability of default, but also to determine the exposure to default and the loss given default. The proposed model was based on a probabilistic regression including independent variables studied by other authors. To confirm the robustness of the model a thorough statistical analysis, and its was developed adjustment, accuracy and validation were tested. It was concluded that the independent variables included in the model, the number of children, credit declined and the deteriorating credit conditions contributed significantly and positively to the probability of default. On the other hand, homeownership contributes to the decrease of the household probability of default.
Credit risk and its measurement are the primary focus of a credit institution, especially since the start of the current financial crisis, which has brought credit constraints to the illiquidity of markets and a large number of defaults observed for firms and individuals. This failure arises from poor measurement of credit risk which translates in financing borrowers with high probabilities of default. This dissertation focuses on the measurement of the household probability of default. We estimate an econometric model to determine a credit rating, based on the data from the Household Finance and Consumption Survey held in 2010, in Portugal. It was possible not only to determine the household probability of default, but also to determine the exposure to default and the loss given default. The proposed model was based on a probabilistic regression including independent variables studied by other authors. To confirm the robustness of the model a thorough statistical analysis, and its was developed adjustment, accuracy and validation were tested. It was concluded that the independent variables included in the model, the number of children, credit declined and the deteriorating credit conditions contributed significantly and positively to the probability of default. On the other hand, homeownership contributes to the decrease of the household probability of default.
Description
Keywords
Crédito Risco de crédito Modelo de notação de risco de crédito e agências de notação de risco de crédito Credit Credit risk Credit scoring model and credit rating agencies