Usage of Artificial Intelligence and Spectral Analysis for Predicting the Behavior of Stock Prices

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216275%3A25530%2F17%3A39911497" target="_blank" >RIV/00216275:25530/17:39911497 - isvavai.cz</a>
Result on the web
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DOI - Digital Object Identifier
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Result language
angličtina
Original language name
Usage of Artificial Intelligence and Spectral Analysis for Predicting the Behavior of Stock Prices
Original language description
In this paper methods of artificial intelligence and spectral analysis to build an algorithm for predicting the behavior of stock prices are applied. Spectral decomposition of a time series was calculated using known methods based on Fourier transformation. The results obtained from periodogram analysis simply provide information about periodicities. Significance analysis was not performed and we worked with four frequencies. This spectral information is then used in clustering of data. Comparison of behavior of price oscillation in clusters was carried out. The presented contribution aims to describe a new algorithm for predicting the behavior of stock prices. The clustering algorithm is based on spectral analysis and SOM. The whole procedure is tested on selected time sections of Dow Jones Industrial Averages, where the algorithm is performed. Results of analysis and final discussion, presented in the Case Study, show that the new method successfully signalizes the trend of stock market prices.
Czech name
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Czech description
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Project
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Continuities
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Publication year
2017
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection
16th Conference on Applied Mathematics APLIMAT 2017 : proceedings
ISBN
978-80-227-4650-2
ISSN
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e-ISSN
neuvedeno
Number of pages
11
Pages from-to
1264-1275
Publisher name
Spektrum STU
Place of publication
Bratislava
Event location
Bratislava
Event date
Jan 31, 2017
Type of event by nationality
EUR - Evropská akce
UT code for WoS article
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