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VaR bounds for joint portfolios with dependence constraints

100%

Puccetti G., Rüschendorf L., Manko D.

Dependence Modeling

2016

tom 4

nr 1

Based on a novel extension of classical Hoeffding-Fréchet bounds, we provide an upper VaR bound for joint risk portfolios with fixed marginal distributions and positive dependence information. The positive dependence information can be assumed to hold in the tails, in some central part, or on a general subset of the domain of the distribution function of a risk portfolio. The newly provided VaR bound can be interpreted as a comonotonic VaR computed at a distorted confidence level and its quality is illustrated in a series of examples of practical interest.

Quantile of a Mixture with Application to Model Risk Assessment

100%

Bernard C., Vanduffel S.

Dependence Modeling

2015

tom 3

nr 1

We provide an explicit expression for the quantile of a mixture of two random variables. The result is useful for finding bounds on the Value-at-Risk of risky portfolios when only partial dependence information is available. This paper complements the work of [4].

Ograniczanie wyników

2 Dependence Modeling

1 Bernard C.

1 Manko D.

1 Puccetti G.

1 Rüschendorf L.

1 Vanduffel S.

1 2016

1 2015

Wyniki wyszukiwania

VaR bounds for joint portfolios with dependence constraints

Quantile of a Mixture with Application to Model Risk Assessment