In this paper we propose a component approach to systemic risk which makes it possible to decompose the risk of the aggregate financial system (measured by Expected Shortfall, ES) while accounting for the level of firm's characteristics. Developed by analogy with the Component Value-at-Risk...

In the context of credit scoring, ensemble methods based on decision trees, suchas the random forest method, provide better classi cation performance than standardlogistic regression models. However, logistic regression remains the benchmark in thecredit risk industry mainly because the lack of...

In this article we propose a multivariate dynamic probit model. Our model can be viewed as a nonlinear VAR model for the latent variables associated with correlated binary time-series data. To estimate it, we implement an exact maximum likelihood approach, hence providing a solution to the...