Model Uncertainty And Scenario Aggregation

This paper provides a coherent method for scenario aggregation addressing model uncertainty. It is based on divergence minimization from a reference probability measure subject to scenario constraints. An example from regulatory practice motivates the definition of five fundamental criteria that serve as a basis for our method. Standard risk measures, such as value-at-risk and expected shortfall, are shown to be robust with respect to minimum divergence scenario aggregation. Various examples illustrate the tractability of our method.


Published in:
Mathematical Finance, 27, 2, 534-567
Year:
2017
Publisher:
Hoboken, Wiley-Blackwell
ISSN:
0960-1627
Keywords:
Laboratories:




 Record created 2017-05-01, last modified 2018-09-13


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