This paper quantifies the credit risk loss distribution of the Spanish financial system using the saddlepoint method. We use the Spanish financial system portfolio built in García-Céspedes and Moreno (2013) to quantify the loss distribution and allocate the risk over the different Spanish...

This paper explores the accuracy of the Taylor expansion based approximations to measure the credit risk loss distribution of the Spanish financial system. We also evaluate the accuracy of the risk allocation under VaR and expected shortfall (ES) criteria obtained with the Taylor expansion based...

This paper quantifies the credit risk loss distribution of the Spanish financial system by introducing a general Monte Carlo importance sampling (IS) approach. We start obtaining all the required information for the Vasicek (1987) model. Then we quantify the loss distribution under the standard...

This paper explores the ability of the Machine Learning (ML) techniques to calibrate models that replicate the outputs of the Vasicek credit risk model. This model measures the loss distribution of a portfolio made up of loans that can be exposed to multiple systemic factors and it is widely...

Financial institutions and regulators usually measure credit risk only over a one-year time horizon. Hence, current statistical models can generate closed-form expressions for the one-year loss distribution. Losses over longer horizons are considered using scenario analysis or Monte Carlo...

This paper proposes an approximate formula to measure the credit risk of portfolios under random recoveries. This formula is based on a Taylor expansion and enables having recoveries that are correlated with the default rates over the business cycle. We show how to calibrate the corresponding...

After the recent financial crisis (2007-2010), many doubts on the reliability of the mathematical models to measure the financial risks have arisen. As a consequence, model risk has been a source of concern for financial regulators. This risk includes, among others, incorrect mathematical...