English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

A fundamental problem in risk management is the robust aggregation ofdifferent sources of risk in a situation where little or no data are availableto infer information about their dependencies. A popular approach to solvingthis problem is to formulate an optimization problem under which one maximizesa risk measure over all multivariate distributions that are consistent with theavailable data. In several special cases of such models, there exist dualproblems that are easier to solve or approximate, yielding robust bounds on theaggregated risk. In this chapter we formulate a general optimization problem,which can be seen as a doubly infinite linear programming problem, and we showthat the associated dual generalizes several well known special cases andextends to new risk management models we propose.

A General Duality Relation with Applications in Quantitative Risk Management