The present study aims at modelling market risk for four commodities, namely West Texas Intermediate (WTI) crude oil … Conditional Auto-Regressive Logit (CARL) models to predict risk measures for the futures return series of the considered … models in order to predict the probability of tail events and the Value-at-Risk and the Expected Shortfall risk measures for …

risk models. We take an analytical point of view and link this function to a partial-integro-differential equation and …

We introduce a neural network approach for assessing the risk of a portfolio of assets and liabilities over a given … value-at-risk and expected shortfall, but the approach also works for other risk measures. …

-dependent features in a regime-switching risk model. In each regime, a binomial discretization of the asset value is obtained by … numerical applications are provided to support the model, which is also useful to accurately capture the market risk concerning …

, which constitute a very important systemic risk factor. Interlinkages between insurers and their dynamics have a direct … impact on systemic risk contagion in the insurance sector. Herein, we propose a new hybrid approach to the analysis of … 2005–2019. The contribution to systemic risk of each institution is determined by analyzing the deltaCoVaR time …