A shadow utility of portfolios efficient with respect to the second order stochastic dominance
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F21%3A10472071" target="_blank" >RIV/00216208:11320/21:10472071 - isvavai.cz</a>
Result on the web
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DOI - Digital Object Identifier
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Alternative languages
Result language
angličtina
Original language name
A shadow utility of portfolios efficient with respect to the second order stochastic dominance
Original language description
We consider diversification-consistent DEA models which are consistent with the second order stochastic dominance (SSD). These models can identify the portfolios which are SSD efficient and suggest the revision of portfolio weights for the inefficient ones. There is also a way how to reconstruct the utility of particular investors based on efficient portfolio which they hold. We apply the above mentioned approaches to industry representative portfolios and discuss the risk aversion of the investors. We focus on the sensitivity with respect to various levels of the risk aversion.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
10103 - Statistics and probability
Result continuities
Project
<a href="/en/project/GX19-28231X" target="_blank" >GX19-28231X: DyMoDiF - Dynamic Models for the Digital Finance</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2021
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
39TH INTERNATIONAL CONFERENCE ON MATHEMATICAL METHODS IN ECONOMICS (MME 2021)
ISBN
978-80-213-3126-6
ISSN
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e-ISSN
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Number of pages
6
Pages from-to
48-53
Publisher name
Czech Univ Life Sciences Prague
Place of publication
Prague 6
Event location
Prague
Event date
Sep 8, 2021
Type of event by nationality
EUR - Evropská akce
UT code for WoS article
000936369700008