to market extreme scenarios, incorporating the need of regulators and financial institutions in more sensitive risk … loss distribution. The findings show that our VaR estimations are able to capture the tail risk and react to market …

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 …

measures of risk. Furthermore, Qα(X ; p) is the optimal value in a certain minimization problem, the minimizers in which are … problems. In finance, Q0(X;p) and Q1(X ; p) are known as the value at risk (VaR) and the conditional value at risk (CVaR). The … sensitivity to risk. The problems of the effective computation of the bounds are considered. Various other related results are …

This article reviews two leading measures of financial risk and an emerging alternative. Embraced by the Basel accords …, value-at-risk and expected shortfall are the leading measures of financial risk. Expectiles offset the weaknesses of value-at-risk … (VaR) and expected shortfall. Indeed, expectiles are the only elicitable law-invariant coherent risk measures. After …

The aim of this paper is to provide several examples of convex risk measures necessary for the application of the … classical portfolio risk measures such as the standard deviation, we, in particular, construct risk measures related to the … and Mahmoud (2017), and Zabarankin, Pavlikov, and Uryasev (2014), who used the absolute drawdown, our risk measure is …

In the present paper, we study quantile risk measures and their domain. Our starting point is that, for a probability … measure Q on the open unit interval and a wide class L Q of random variables, we define the quantile risk measure ϱ Q as the … quantile risk measure is a natural generalization of that of a spectral risk measure and provides another view of the …

An accurate assessment of the risk of extreme environmental events is of great importance for populations, authorities … and the banking/insurance/reinsurance industry. Koch (2017) introduced a notion of spatial risk measure and a … corresponding set of axioms which are well suited to analyze the risk due to events having a spatial extent, precisely such as …

Evaluating risk measures, premiums, and capital allocation based on dependent multi-losses is a notoriously difficult … by a heavy-tailed background risk. A particular attention is given to the distortion and weighted risk measures and … allocations, as well as their special cases such as the conditional layer expectation, tail value at risk, and the truncated tail …

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 …