%X The forecasting of the stock markets' trends is one of the most frequently applied point of interests in machine learning (ML) industry 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.
%K Costs; Decision trees; Electronic trading; Financial markets; Forecasting; Support vector machines, Fibonacci ratios; Ml algorithms; Pattern detectors; Point of interest; Random forests; Trading strategies; Trend forecasting; Trend prediction, Commerce
%O cited By 1; Conference of 1st EAI International Conference on Computer Science and Engineering, COMPSE 2016 ; Conference Date: 11 November 2016 Through 12 November 2016; Conference Code:130814
%L scholars8820
%J COMPSE 2016 - 1st EAI International Conference on Computer Science and Engineering
%D 2017
%R 10.4108/eai.27-2-2017.152341
%T Market prices trend forecasting supported by Elliott Wave's theory
%A T. Vantuch
%A I. Zelinka
%A P. Vasant
%I EAI