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dc.contributor.author | Zhalgasbek, Ayaz![]() |
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dc.date.accessioned | 2023-06-16T09:10:12Z | |
dc.date.available | 2023-06-16T09:10:12Z | |
dc.date.issued | 2023 | |
dc.identifier.citation | Zhalgasbek, Aю (2023). Analysis of Elliott Wave theory on time-series data from Forex. School of Sciences and Humanities | en_US |
dc.identifier.uri | http://nur.nu.edu.kz/handle/123456789/7226 | |
dc.description.abstract | This capstone project analyzes the application of the Elliott wave theory on time-series data from the Forex market. The project uses patternbased probabilistic models to test the validity of the Elliott wave theory and to evaluate its predictive power. The results of our analysis indicate that the pattern-based probabilistic models do not completely support the Elliott wave theory. Specifically, we found that the patterns identified by the Elliott wave theory did not have statistically significant predictive power for daily exchange rates of currencies. This study encourages further research on this topic with different criteria and larger data sets | en_US |
dc.language.iso | en | en_US |
dc.publisher | School of Sciences and Humanities | en_US |
dc.rights | Attribution-NonCommercial-ShareAlike 3.0 United States | * |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-sa/3.0/us/ | * |
dc.subject | Type of access: Restricted | en_US |
dc.subject | Elliott wave theory | en_US |
dc.title | ANALYSIS OF ELLIOTT WAVE THEORY ON TIME-SERIES DATA FROM FOREX | en_US |
dc.type | Master's thesis | en_US |
workflow.import.source | science |
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