Investment portfolio optimization based on genetic algorithm
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26510%2F11%3APU92406" target="_blank" >RIV/00216305:26510/11:PU92406 - 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
Investment portfolio optimization based on genetic algorithm
Original language description
The paper describes creation and application of an investment portfolio. For the creating an investment portfolio is used technical approach supported by statistical analysis. Main aim of the paper is to perform statistical analysis of selected financialinstruments and to find connections between the input data using application Adaptrade from Adaptrade Software Company. This application is based on genetic algorithms basis and is able to process this difficult task in real time. Application of geneticalgorithms in developing a model of investment portfolio allows sophisticated analysis and searching of relevant information in the input data than standard algorithmic methods. Genetic algorithms find a more sensitive set of rules for entry, exit and management of speculative positions. The added value of the application of genetic algorithms is sensible setting of the investment portfolio parameters. The case analysis is performed for three world currencies (U.S. dollar, Euro and Brit
Czech name
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Czech description
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Classification
Type
J<sub>x</sub> - Unclassified - Peer-reviewed scientific article (Jimp, Jsc and Jost)
CEP classification
AE - Management, administration and clerical work
OECD FORD branch
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Result continuities
Project
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Continuities
S - Specificky vyzkum na vysokych skolach
Others
Publication year
2011
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
1st international scientific concerence "Practice and research in private public sector-11"
ISSN
2029-7378
e-ISSN
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Volume of the periodical
1
Issue of the periodical within the volume
1
Country of publishing house
LT - LITHUANIA
Number of pages
360
Pages from-to
134-141
UT code for WoS article
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EID of the result in the Scopus database
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