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@article{55465, author = {Šuleř, Petr and Machová, Veronika}, article_location = {Poland}, article_number = {2}, doi = {http://dx.doi.org/10.14254/2071-8330.2020/13-2/18}, keywords = {time series; prediction; share prices; artificial neural networks; exponential smoothing; Prague Stock Exchange}, language = {eng}, issn = {2071-8330}, journal = {Journal of International Studies}, title = {Better results of artificial neural networks in predicting ČEZ share prices}, url = {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-}, volume = {13}, year = {2020} }
TY - JOUR ID - 55465 AU - Šuleř, Petr - Machová, Veronika PY - 2020 TI - Better results of artificial neural networks in predicting ČEZ share prices JF - Journal of International Studies VL - 13 IS - 2 SP - 259-278 EP - 259-278 PB - Centre of Sociological Research SN - 20718330 KW - time series KW - prediction KW - share prices KW - artificial neural networks KW - exponential smoothing KW - Prague Stock Exchange UR - 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- L2 - 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- N2 - 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. ER -
ŠULEŘ, Petr and Veronika MACHOVÁ. Better results of artificial neural networks in predicting ČEZ share prices. \textit{Journal of International Studies}. Poland: Centre of Sociological Research, vol.~13, No~2, p.~259-278. ISSN~2071-8330. doi:10.14254/2071-8330.2020/13-2/18. 2020.
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