With the advent of Basel II, risk-capital provisions need to also account for operational risk. The specification of dependence structures and the assessment of their effects on aggregate risk-capital are still open issues in modeling operational risk. In this paper, we investigate the potential...

Abstract. We show that the use of correlations for modeling dependencies may lead to counterintuitive behavior of risk measures, such as Value-at-Risk (VaR) and Expected Short- fall (ES), when the risk of very rare events is assessed via Monte-Carlo techniques. The phenomenon is demonstrated for...

We show that the use of correlations for modeling dependencies may lead to counterintuitive behavior of risk measures, such as Value-at-Risk (VaR) and Expected Shortfall (ES), when the risk of very rare events is assessed via Monte-Carlo techniques. The phenomenon is demonstrated for mixture...

Being still in its early stages, operational risk modeling has, so far, mainly been concentrated on the marginal distributions of frequencies and severities within the context of the Loss Distribution Approach (LDA). A realistic quantitative model, however, should be capable of modeling the...

High levels of correlation among financial assets, as well as extreme losses, are typical during crisis periods. In such situations, quantitative asset allocation models are often not robust enough to deal with estimation errors and lead to identifying underperforming investment strategies. It...

Highlights:• State-of-art review of vine copulas and stationary vine copulas.• Two types of vine copula models to capture cross-sectional and temporal dependence in ESG data.• Extreme ESG classes (i.e., classes A and D) show the highest and nonGaussian dependence to the market.• Future...

Climate change and sustainability have become societal focal points in the last decade. Consequently, companies have been increasingly characterized by non-financial information, such as environmental, social, and governance (ESG) scores, based on which companies can be grouped into ESG classes....

We propose the use of state-space models (SSMs) to estimate dynamic spatial relationships from time series data. At each time step, the weight matrix, capturing the latent state, is updated by a spatial autoregressive model. Specifically, we consider two types of SSM: the first one calibrates...