An algorithm for Elliott Waves pattern detection
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F18%3A10241920" target="_blank" >RIV/61989100:27240/18:10241920 - isvavai.cz</a>
Alternative codes found
RIV/61989100:27740/18:10241920
Result on the web
<a href="https://content.iospress.com/articles/intelligent-decision-technologies/idt319" target="_blank" >https://content.iospress.com/articles/intelligent-decision-technologies/idt319</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.3233/IDT-170319" target="_blank" >10.3233/IDT-170319</a>
Alternative languages
Result language
angličtina
Original language name
An algorithm for Elliott Waves pattern detection
Original language description
The examination of the ElliottWave theory is the main motivation of this contribution. All of the fundamental features of an proper ElliottWave pattern (EW pattern) are reviewed and explained. Based on this knowledge, an algorithm for detection of these patterns is designed, developed and tested. Under several different algorithm settings, several EW pattern sets are obtained. They differ in amount of found EW patterns, quality and size. The following application of the developed detection algorithm was based on recognition of an incomplete EW patterns with aim of the prediction of the following progress of the time set. The Random Decision Forest and the Support Vector Machine are the machine learning algorithms employed for this task. The accuracy of trend prediction above 70% proves the relevancy of EW patterns on stock market data as well as the validity of the algorithm as a tool for detection of such patterns.
Czech name
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Czech description
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Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
<a href="/en/project/GA15-06700S" target="_blank" >GA15-06700S: Unconventional Control of Complex Systems</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2018
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
Intelligent Decision Technologies
ISSN
1872-4981
e-ISSN
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Volume of the periodical
12
Issue of the periodical within the volume
1
Country of publishing house
NL - THE KINGDOM OF THE NETHERLANDS
Number of pages
10
Pages from-to
15-24
UT code for WoS article
000445796700003
EID of the result in the Scopus database
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