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dc.contributor.authorDokuchaev, Nikolai
dc.date.accessioned2017-07-27T05:20:10Z
dc.date.available2017-07-27T05:20:10Z
dc.date.created2017-07-26T11:11:19Z
dc.date.issued2017
dc.identifier.citationDokuchaev, N. 2017. On the structure of multifactor optimal portfolio strategies. European Series in Applied and Industrial Mathematics: Control, Optimisation and Calculus of Variations (ESAIM COCV). 24 (3): pp. 1043-1058.
dc.identifier.urihttp://hdl.handle.net/20.500.11937/54223
dc.identifier.doi10.1051/cocv/2017013
dc.description.abstract

The paper studies problem of optimal portfolio selection. It is shown that, under some mild conditions, near optimal strategies for investors with different performance criteria can be constructed using a limited number of fixed processes (mutual funds), for a market with a larger number of available risky stocks. This implies dimension reduction for the optimal portfolio selection problem: all rational investors may achieve optimality using the same mutual funds plus a saving account. This result is obtained under mild restrictions for the utility functions without any assumptions on regularity of the value function. The proof is based on the method of dynamic programming applied indirectly to some convenient approximations of the original problem that ensure certain regularity of the value functions. To overcome technical difficulties, we use special time dependent and random constraints for admissible strategies such that the corresponding HJB (Hamilton–Jacobi–Bellman) equation admits “almost explicit” solutions generating near optimal admissible strategies featuring sufficient regularity and integrability.

dc.publisherEDP Sciences
dc.titleOn the structure of multifactor optimal portfolio strategies
dc.typeJournal Article
dcterms.source.volume24
dcterms.source.startPage1043
dcterms.source.endPage1058
dcterms.source.issn1292-8119
dcterms.source.titleEuropean Series in Applied and Industrial Mathematics: Control, Optimisation and Calculus of Variations (ESAIM COCV)
curtin.departmentDepartment of Mathematics and Statistics
curtin.accessStatusFulltext not available


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