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In this paper, following the generalization of Delta Normal VaR to Delta Mixture Elliptic VaR in Sadefo-Kamdem [3], we give and explicit formula to estimate linear VaR and ES when the risk factors changes with the mixture of t-Student distributions. In particular, we give rise to Delta-Mixture-Student VaR and the Delta-Mixture-Elliptic ES.

Generally, in the financial literature, the notion of quadratic VaR is implicitly confused with the Delta-Gamma VaR, because more authors dealt with portfolios that contained derivatives instruments. In this paper, we postpone to estimate both the expected shortfall and Value-at-Risk of a quadratic portfolio of securities (i.e equities) without the Delta and Gamma Greeks, when the joint log-ret...

The conditional tail expectation in risk analysis describes the expected amount of risk that can be experienced given that a potential risk exceeds a threshold value, and provides an important measure for right-tail risk. In this paper, we study the convolution and extreme values of dependent risks that follow a multivariate phase type distribution, and derive explicit formulas of several condi...

This paper compares three value-at-risk approximation methods suggested in the literature: Cornish-Fisher (1937), Sillitto (1969), and Liu (2010). Simulation results are obtained for three families of distributions: student-t, skewed-normal, and skewed-t. We recommend the Sillitto approximation as the best method to evaluate the value at risk when the financial return has an unknown, skewed, an...

rule ClassWithOperationsContributingClass merge c : Core!EClass with s : ObserverPattern!EClass into t : Target!EClass { for (sop in s.eOperations) { var op : new Target!EOperation; op.name := sop.name; t.eOperations.add(op); for (sopp in sop.eParameters) { var p : new Target!EParameter; p.name := sopp.name; p.eType ::= sopp.eType; op.eParameters.add(p); } } } auto rule ClassWithObserver merge ...