We propose a new method for analysing multiperiod stress scenarios for portfolio credit risk more systematically than in the current practice of macro stress testing. Our method quantifies the plausibility of scenarios by considering the distance of the stress scenario from an average scenario....

We propose a new method for analysing multi-period stress scenarios for portfolio credit risk more systematically than in current macro stress tests. The plausibility of a scenario is quantified by its distance from an average scenario. For a given level of plausibility, we search systematically...

Utilizando datos granulares de la Central de Información de Riesgos del Banco de España, estudiamos uno de los canales de contagio a través de los cuales se pueden transmitir las tensiones en los mercados financieros —el canal de la calidad crediticia—, enfocándonos en el mercado...

Informes recientes muestran la creciente adopción en el sector financiero de técnicas de aprendizaje automático o machine learning (ML) en la gestión del riesgo de crédito. En este entorno, los supervisores se encuentran ante el reto de permitir que se maximicen las oportunidades derivadas...

This paper develops a flexible and computationally efficient model to estimate the credit loss distribution of the loans in a banking system. We consider a sectorial structure, where default frequencies and the total number of loans are allowed to depend on macroeconomic conditions as well as on...

This paper analyses the risk and return of loans portfolios in a joint setting. I develop a model to obtain the distribution of loans returns. I use this model to describe the investment opportunity set of lenders using mean-variance analysis with a Value at Risk constraint. I also obtain closed...

A common assumption in the academic literature is that franchise value plays a key role in limiting bank risk-taking. As market power is the primary source of franchise value, reduced competition in banking markets has been seen as promoting banking stability. We test this hypothesis using data...

Model uncertainty hampers consensus on the main determinants of corporate default. We employ Bayesian model averaging (BMA) techniques in order to shed light on this issue. Empirical findings suggest that the most robust determinants of corporate default are firm-specific variables such as the...

Incluye bibliografía ; This article estimates a general credit risk model with both macroeconomic and latent credit factors for Spanish banks during the period 2004-2010. The proposed framework allows to estimate with bank level data both the standard credit risk model of Basel II and...