A duality approach to the worst case value at risk for a sum of dependent random variables with known covariances
We propose an approach to the aggregation of risks which is based on estimation of simple quantities (such as covariances) associated to a vector of dependent random variables, and which avoids the use of parametric families of copulae. Our main result demonstrates that the method leads to bounds on the worst case Value at Risk for a sum of dependent random variables. Its proof applies duality theory for infinite dimensional linear programs.
Year of publication: |
2009-12
|
---|---|
Authors: | Franke, Brice ; Stolz, Michael |
Institutions: | arXiv.org |
Saved in:
freely available
Saved in favorites
Similar items by person
-
Gaussian fluctuations for sample covariance matrices with dependent data
Friesen, Olga, (2013)
-
Stolz, Michael, (1966)
-
Change point testing for the drift parameters of a periodic mean reversion process
Dehling, Herold, (2014)
- More ...