First EAI International Conference on Computer Science and Engineering

Research Article

Market Prices Trend Forecasting Supported By Elliott Wave’s Theory

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  • @INPROCEEDINGS{10.4108/eai.27-2-2017.152341,
        author={Tomas Vantuch and Ivan Zelinka and Pandian Vasant},
        title={Market Prices Trend Forecasting Supported By Elliott Wave’s Theory},
        proceedings={First EAI International Conference on Computer Science and Engineering},
        publisher={EAI},
        proceedings_a={COMPSE},
        year={2017},
        month={3},
        keywords={Elliott waves Fibonacci ratios Support Vector Machine Random Forest Stock Markets},
        doi={10.4108/eai.27-2-2017.152341}
    }
    
  • Tomas Vantuch
    Ivan Zelinka
    Pandian Vasant
    Year: 2017
    Market Prices Trend Forecasting Supported By Elliott Wave’s Theory
    COMPSE
    EAI
    DOI: 10.4108/eai.27-2-2017.152341
Tomas Vantuch1,*, Ivan Zelinka, Pandian Vasant
  • 1: Department of Computer Science, VSB-Technical University of Ostrava, 17. listopadu 15 708 33, Ostrava-Poruba, Czech Republic
*Contact email: tomas.vantuch@vsb.cz

Abstract

The forecasting of the stock markets’ trends is one of the most frequently applied point of interests in machine learning (ML) in-dustry from its beginning. The theory of Elliott waves’ (EW) patterns based on Fibonacci’s ratios is also heavily applied in several trading strategies and tools which are available on the market and also there are many studies based on analysis and application of those patterns. This paper covers market’s trend prediction by ML algorithms such as Random Forest and Support Vector Machine. The trend prediction is supported by application of recognized Elliot waves which was performed by custom developed algorithm based on available knowledge about the patterns. The combination of ML algorithms and EW pattern detector achieved significantly higher performance compare to the ML algorithms only.