ALM models based on second order stochastic dominance
Maram Alwohaibi () and
Diana Roman
Additional contact information
Maram Alwohaibi: Brunel University London
Diana Roman: Brunel University College of Engineering Design and Physical Sciences
Computational Management Science, 2018, vol. 15, issue 2, No 4, 187-211
Abstract:
Abstract We propose asset and liability management 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. 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.
Date: 2018
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)
Downloads: (external link)
http://link.springer.com/10.1007/s10287-018-0299-8 Abstract (text/html)
Access to the full text of the articles in this series is restricted.
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:spr:comgts:v:15:y:2018:i:2:d:10.1007_s10287-018-0299-8
Ordering information: This journal article can be ordered from
http://www.springer. ... ch/journal/10287/PS2
DOI: 10.1007/s10287-018-0299-8
Access Statistics for this article
Computational Management Science is currently edited by Ruediger Schultz
More articles in Computational Management Science from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().