Multistage portfolio optimization with multivariate dominance constraints
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F19%3A10401758" target="_blank" >RIV/00216208:11320/19:10401758 - isvavai.cz</a>
Result on the web
<a href="https://verso.is.cuni.cz/pub/verso.fpl?fname=obd_publikace_handle&handle=HYMvlUX8tI" target="_blank" >https://verso.is.cuni.cz/pub/verso.fpl?fname=obd_publikace_handle&handle=HYMvlUX8tI</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/s10287-018-0334-9" target="_blank" >10.1007/s10287-018-0334-9</a>
Alternative languages
Result language
angličtina
Original language name
Multistage portfolio optimization with multivariate dominance constraints
Original language description
In this article we focus on multistage portfolio optimization problem with usage of multivariate stochastic dominance constraints. The first part of the work is devoted to the theoretical background needed for establishing the optimization problem. We provide a general approach to multivariate stochastic dominance, we mainly recall basic definitions and several statements that are relevant for portfolio optimization, and describe an algorithm for detecting multivariate stochastic dominance of two random vectors with discrete distributions. The main part of the work introduces multivariate stochastic dominance constraints in multistage portfolio optimization problem. We compare obtained results with traditional model which employs univariate first order stochastic dominance constraints at each stage.
Czech name
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Czech description
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Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
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OECD FORD branch
10103 - Statistics and probability
Result continuities
Project
<a href="/en/project/GBP402%2F12%2FG097" target="_blank" >GBP402/12/G097: DYME-Dynamic Models in Economics</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2019
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
Computational Management Science
ISSN
1619-697X
e-ISSN
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Volume of the periodical
16
Issue of the periodical within the volume
1-2
Country of publishing house
DE - GERMANY
Number of pages
30
Pages from-to
17-46
UT code for WoS article
000458627300003
EID of the result in the Scopus database
2-s2.0-85052490073