Please use this identifier to cite or link to this item: http://bura.brunel.ac.uk/handle/2438/16215
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dc.contributor.authorAlwohaibi, M-
dc.contributor.authorRoman, D-
dc.date.accessioned2018-05-22T11:15:58Z-
dc.date.available2018-03-08-
dc.date.available2018-05-22T11:15:58Z-
dc.date.issued2018-
dc.identifier.citationComputational Management Science, 2018, pp. 1 - 25en_US
dc.identifier.issn1619-697X-
dc.identifier.issnhttp://dx.doi.org/10.1007/s10287-018-0299-8-
dc.identifier.issnhttp://dx.doi.org/10.1007/s10287-018-0299-8-
dc.identifier.issnhttp://dx.doi.org/10.1007/s10287-018-0299-8-
dc.identifier.urihttp://bura.brunel.ac.uk/handle/2438/16215-
dc.description.abstractWe propose asset and liability management (ALM) models in which the risk of underfunding is modelled based on the concept of stochastic dominance. Investment decisions are taken such that the distribution of the funding ratio, that is, the ratio of asset to liabilities, is non-dominated with respect to second order stochastic dominance (SSD). In addition, the funding ratio distribution is close in an optimal sense to a user-specified target distribution. Interesting results are obtained when the target distribution is degenerate; in this case, we can obtain equivalent risk minimisation models, with risk defined as expected shortfall or as worst case loss. As an application, we consider the financial planning problem of a defined benefit pension fund in Saudi Arabia.en_US
dc.format.extent1 - 25-
dc.language.isoenen_US
dc.publisherSpringer Verlagen_US
dc.titleALM models based on second order stochastic dominanceen_US
dc.typeArticleen_US
dc.identifier.doihttp://dx.doi.org/10.1007/s10287-018-0299-8-
dc.relation.isPartOfComputational Management Science-
pubs.publication-statusPublished online-
Appears in Collections:Dept of Mathematics Research Papers

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