A fractal structure of time series and prediction (a comparative study to neural network)
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61988987%3A17310%2F10%3AA1100YDC" target="_blank" >RIV/61988987:17310/10:A1100YDC - 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
A fractal structure of time series and prediction (a comparative study to neural network)
Original language description
We develop two models for analysis and forecasting of financial time series. The first model is based on Elliott waves, which disposes of fractal structure. The second one uses an artificial neural network that is adapted by backpropagation. The Elliottwave principle is a detailed description of how financial markets behave. Artificial neural networks are suitable for predicting time series because are able to generalize and are resistant to noise. This paper also includes experimental results of timeseries prediction carried out with both mentioned models.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
IN - Informatics
OECD FORD branch
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Result continuities
Project
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Continuities
S - Specificky vyzkum na vysokych skolach
Others
Publication year
2010
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Mendel 2010
ISBN
978-80-214-4120-0
ISSN
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e-ISSN
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Number of pages
6
Pages from-to
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Publisher name
Brno Univerzity of Technology
Place of publication
Brno
Event location
Brno
Event date
Jun 23, 2010
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
000288144100020