Research Article
Market Prices Trend Forecasting Supported By Elliott Wave’s Theory
@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
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.
