TY  - CONF
PB  - EAI
SN  - 9781631901362
Y1  - 2017///
A1  - Vantuch, T.
A1  - Zelinka, I.
A1  - Vasant, P.
UR  - https://www.scopus.com/inward/record.uri?eid=2-s2.0-85085405496&doi=10.4108%2feai.27-2-2017.152341&partnerID=40&md5=e22794d9c01939a1b48e0fc8f0700aa9
AV  - none
TI  - Market prices trend forecasting supported by Elliott Wave's theory
ID  - scholars8820
KW  - Costs; Decision trees; Electronic trading; Financial markets; Forecasting; Support vector machines
KW  -  Fibonacci ratios; Ml algorithms; Pattern detectors; Point of interest; Random forests; Trading strategies; Trend forecasting; Trend prediction
KW  -  Commerce
N2  - 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.
N1  - 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
ER  -