In this paper, the generalized Pareto distribution (GPD) copula approach is utilized to solve the conditional value-at-risk …-parametric kernel-smoothed interior and the parametric Pareto upper tail and (iii) Value-at-Risk (VaR) to quantify risk measure. The … minimizing CVaR measure and simulated copula returns combined outperforms the risk/return of domestic portfolios, such as the US …

such policies. A typical industry practice consists of using fund mapping regressions to represent basis risk stemming from …

In this paper, we propose a novel framework for estimating systemic risk measures and risk allocations based on Markov … Chain Monte Carlo (MCMC) methods. We consider a class of allocations whose jth component can be written as some risk measure … intersection of linear constraints, this class of allocations covers, for example, conditional Value-at-Risk (CoVaR), conditional …

The present article deals with intra-horizon risk in models with jumps. Our general understanding of intra-horizon risk … quantifying market risk by strictly relying on point-in-time measures cannot be deemed a satisfactory approach in general. Instead …, we argue that complementing this approach by studying measures of risk that capture the magnitude of losses potentially …

We introduce a class of quantile-based risk measures that generalize Value at Risk (VaR) and, likewise Expected … probability of occurrence. The corresponding risk measure, called Loss VaR (LVaR), determines the minimal capital injection that … and applications to capital adequacy, portfolio risk management and catastrophic risk are presented …

on various methods of the optimal tail selection in risk measurement. The results indicate which method may be useful in … objective is to compare the methods and to identify those which can be recognized as useful in risk measurement. The results …

This paper proposes a new method to introduce coherent risk measures for risks with infinite expectation, such as those … characterized by some Pareto distributions. Extensions of the conditional value at risk, the weighted conditional value at risk and …

When the uni-variate risk measure analysis is generalized into the multi-variate setting, many complex theoretical and … applied problems arise, and therefore the mathematical models used for risk quantification usually present model risk. As a … task, we propose a novel multi-variate risk measure, based on the notion of the Wasserstein barycenter. The proposed …

When the uni-variate risk measure analysis is generalized into the multi-variate setting, many complex theoretical and … applied problems arise, and therefore the mathematical models used for risk quantification usually present model risk. As a … task, we propose a novel multi-variate risk measure, based on the notion of the Wasserstein barycenter. The proposed …