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Please use this identifier to cite or link to this item: https://hdl.handle.net/2440/88723
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dc.contributor.authorSeck, B.-
dc.contributor.authorElliott, R.-
dc.contributor.authorGueyie, J.-
dc.date.issued2013-
dc.identifier.citationInternational Journal of Financial Engineering and Risk Management, 2013; 1(4):334-354-
dc.identifier.issn2049-0909-
dc.identifier.issn2049-0917-
dc.identifier.urihttp://hdl.handle.net/2440/88723-
dc.description.abstractDifferent approaches to defining dynamic market risk measures are available in the literature. Most are focused or derived from probability theory, economic behavior or dynamic programming. Here, we propose an approach to define and implement dynamic market risk measures based on recursion and state economy representation. The proposed approach is to be implementable and to inherit properties from static market risk measures.-
dc.description.statementofresponsibilityBabacar Seck, Robert J. Elliott, Jean-Pierre Gueyie-
dc.language.isoen-
dc.publisherInderscience Publishers-
dc.source.urihttp://dx.doi.org/10.1504/ijferm.2014.065649-
dc.subjectDynamic risk measures; Markov Chain; Value-at-Risk; Conditional Value-at-Risk-
dc.titleComputational dynamic market risk measures in discrete time setting-
dc.typeJournal article-
dc.identifier.doi10.1504/IJFERM.2014.065649-
pubs.publication-statusPublished-
Appears in Collections:Aurora harvest 7
Mathematical Sciences publications

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