Comparison of exponential time series alignment and time series alignment using artificial neural networks by example of prediction of future development of stock prices of a specific company
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F75081431%3A_____%2F19%3A00001518" target="_blank" >RIV/75081431:_____/19:00001518 - isvavai.cz</a>
Result on the web
<a href="http://dx.doi.org/10.1051/shsconf/20196101006" target="_blank" >http://dx.doi.org/10.1051/shsconf/20196101006</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1051/shsconf/20196101006" target="_blank" >10.1051/shsconf/20196101006</a>
Alternative languages
Result language
angličtina
Original language name
Comparison of exponential time series alignment and time series alignment using artificial neural networks by example of prediction of future development of stock prices of a specific company
Original language description
The aim of this paper is to compare a method of exponential time series alignment and time series alignment using artificial neural networks as tools for predicting future stock price developments on the example of the company Unipetrol. Time series alignment is performed using artificial neural networks, exponential alignment of time series, and then a comparison of time series of predictions of future stock price trends predicted using the most successful neural network and price prediction calculated by exponential time series alignment is performed.
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
50202 - Applied Economics, Econometrics
Result continuities
Project
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Continuities
N - Vyzkumna aktivita podporovana z neverejnych zdroju
Others
Publication year
2019
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
SHS Web of Conferences: Innovative Economic Symposium 2018 - Milestones and Trends of World Economy (IES2018)
ISBN
9782759890637
ISSN
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e-ISSN
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Number of pages
13
Pages from-to
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Publisher name
EDP Sciences
Place of publication
Les Ulis, France
Event location
Beijing, PR China
Event date
Nov 8, 2018
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
000467727800006