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dc.contributor.authorEvstigneev, Igor
dc.contributor.authorHens, Thorsten
dc.contributor.authorPotapova, Valeriya
dc.contributor.authorSchenk-Hoppé, Klaus R.
dc.date.accessioned2020-12-22T09:48:14Z
dc.date.available2020-12-22T09:48:14Z
dc.date.created2020-12-02T08:54:02Z
dc.date.issued2020
dc.identifier.citationJournal of Mathematical Economics. 2020, 91 121-135.en_US
dc.identifier.issn0304-4068
dc.identifier.urihttps://hdl.handle.net/11250/2720724
dc.description.abstractThis paper analyzes a dynamic stochastic equilibrium model of an asset market based on behavioral and evolutionary principles. The core of the model is a non-traditional game-theoretic framework combining elements of stochastic dynamic games and evolutionary game theory. Its key characteristic feature is that it relies only on objectively observable market data and does not use hidden individual agents’ characteristics (such as their utilities and beliefs). A central goal of the study is to identify an investment strategy that allows an investor to survive in the market selection process, i.e., to keep with probability one a strictly positive, bounded away from zero share of market wealth over an infinite time horizon, irrespective of the strategies used by the other players. The main results show that under very general assumptions, such a strategy exists, is asymptotically unique and easily computableen_US
dc.language.isoengen_US
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 Internasjonal*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/deed.no*
dc.subjectevolutionary financeen_US
dc.subjectbehavioral financeen_US
dc.subjectstochastic dynamic gamesen_US
dc.subjectDSGEen_US
dc.subjectsurvival porfolio rulesen_US
dc.titleBehavioral equilibrium and evolutionary dynamics in asset marketsen_US
dc.typePeer revieweden_US
dc.typeJournal articleen_US
dc.description.versionpublishedVersionen_US
dc.source.pagenumber121-135en_US
dc.source.volume91en_US
dc.source.journalJournal of Mathematical Economicsen_US
dc.identifier.doi10.1016/j.jmateco.2020.09.004
dc.identifier.cristin1855148
cristin.ispublishedtrue
cristin.fulltextoriginal
cristin.qualitycode1


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Attribution-NonCommercial-NoDerivatives 4.0 Internasjonal
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