Tehnički vjesnik, Vol. 25 No. 4, 2018.
Izvorni znanstveni članak
https://doi.org/10.17559/TV-20160318145514
An Automated System for Stock Market Trading Based on Logical Clustering
Aleksandar Rakićević
orcid.org/0000-0002-8917-7229
; University of Belgrade, Faculty of Organizational Sciences, Jove Ilića 154, 11000 Belgrade, Serbia
Vlado Simeunović
; University of Istočno Sarajevo, Faculty of Education in Bijeljina, Semberskih ratara bb, 76300 Bijeljina, Bosnia and Herzegovina
Bratislav Petrović
; University of Belgrade, Faculty of Organizational Sciences, Jove Ilića 154, 11000 Belgrade, Serbia
Sanja Milić
; University of Istočno Sarajevo, Faculty of Education in Bijeljina, Semberskih ratara bb, 76300 Bijeljina, Bosnia and Herzegovina
Sažetak
In this paper a novel clustering-based system for automated stock market trading is introduced. It relies on interpolative Boolean algebra as underlying mathematical framework used to construct logical clustering method which is the central component of the system. The system uses fundamental analysis ratios, more precisely market valuation ratios, as clustering variables to differentiate between undervaluated and overvaluated stocks. To structure investment portfolio, the proposed system uses special weighting formulas which automatically diversify investment funds. Finally, a simple trading simulation engine is developed to test our system on real market data. The proposed system was tested on Belgrade Stock Exchange historical data and was able to achieve a high rate of return and to outperform the BelexLine market index as a benchmark variable. The paper has also provided in-depth analysis of the system’s investment decision making process which reveals some exciting insights.
Ključne riječi
automated trading system; fundamental analysis; linterpolative Boolean algebra; ogical clustering; stock market
Hrčak ID:
204440
URI
Datum izdavanja:
20.8.2018.
Posjeta: 3.066 *