Quantum-inspired meta-heuristic approaches for a constrained portfolio optimization problem
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F24%3A10260361" target="_blank" >RIV/61989100:27240/24:10260361 - isvavai.cz</a>
Result on the web
<a href="https://link.springer.com/article/10.1007/s12065-024-00929-4" target="_blank" >https://link.springer.com/article/10.1007/s12065-024-00929-4</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/s12065-024-00929-4" target="_blank" >10.1007/s12065-024-00929-4</a>
Alternative languages
Result language
angličtina
Original language name
Quantum-inspired meta-heuristic approaches for a constrained portfolio optimization problem
Original language description
Portfolio optimization has long been a challenging proposition and a widely studied topic in finance and management. It involves selecting and allocating the right assets according to the desired objectives. It has been found that this nonlinear constraint problem cannot be effectively solved using a traditional approach. This paper covers and compares quantum-inspired versions of four popular evolutionary techniques with three benchmark datasets. Genetic algorithm, differential evolution, particle swarm optimization, ant colony optimization, and their quantum-inspired incarnations are implemented, and the results are compared. Experiments have been carried out with more than 10 years of stock price data from NASDAQ, BSE, and Dow Jones. This work proposes several enhancements to allocate funds efficiently, such as improved crossover techniques and dynamic and adaptive selection of parameters. Furthermore, it is observed that the quantum-inspired techniques outperform the classical counterparts.
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
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
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Continuities
S - Specificky vyzkum na vysokych skolach
Others
Publication year
2024
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
Evolutionary Intelligence
ISSN
1864-5909
e-ISSN
1864-5917
Volume of the periodical
17
Issue of the periodical within the volume
March
Country of publishing house
DE - GERMANY
Number of pages
40
Pages from-to
nestránkováno
UT code for WoS article
001190462000003
EID of the result in the Scopus database
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