Better results of artificial neural networks in predicting ČEZ share prices

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F75081431%3A_____%2F20%3A00001826" target="_blank" >RIV/75081431:_____/20:00001826 - isvavai.cz</a>
Result on the web
<a href="https://www.scopus.com/record/display.uri?eid=2-s2.0-85090721333&origin=resultslist&sort=plf-f&src=s&st1=Better+results+of+artificial+neural+networks+in+predicting+%c4%8cEZ+share+prices&st2=&sid=37c3a606ab869c5c581bd24e508f36dc&sot=b&sdt=b&sl=90&s=TITLE-" target="_blank" >https://www.scopus.com/record/display.uri?eid=2-s2.0-85090721333&origin=resultslist&sort=plf-f&src=s&st1=Better+results+of+artificial+neural+networks+in+predicting+%c4%8cEZ+share+prices&st2=&sid=37c3a606ab869c5c581bd24e508f36dc&sot=b&sdt=b&sl=90&s=TITLE-</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.14254/2071-8330.2020/13-2/18" target="_blank" >10.14254/2071-8330.2020/13-2/18</a>

Result language
angličtina
Original language name
Better results of artificial neural networks in predicting ČEZ share prices
Original language description
The specific objective of the article is to propose a methodology for predicting future price development of the ČEZ, a.s., share prices on Prague Stock Exchange using artificial neural networks and time series exponential smoothing to validate the results on a part of the time series, and to compare the success rate of these two methods. The data used in our analysis is the data on the share prices for the period of 2014-2019. Multilayer perceptron (MLP) and radial basis function (RBF) networks are generated, with the time series time lag of 1, 5, and 10 days.
Czech name
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Czech description
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Type
J<sub>SC</sub> - Article in a specialist periodical, which is included in the SCOPUS database
CEP classification
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OECD FORD branch
50200 - Economics and Business

Publication year
2020
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

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