Trend analysis with use of binary representation

Michał Stasiak


One of the basic methods of technical analysis is the trend analysis. There are many indicators that allow for a current trend detection and parameter specification based on the candlestick chart representation. Because the use of candlestick representation is characterized by lower informative value, i.e. leads to a loss of information about the course trajectory, better modelling effects can be obtained by using a binary representation. The binarization algorithm transforms the course represented by tick data into a corresponding binary sequence. In the article are proposed algorithm allowing for a detection of current trend and specification of its parameters using binary representation. As a result of the algorithm performance we obtain, for each change in the binary representation, the type of the current trend and its parameters, resulting in a so-called binary-trend representation of a course trajectory. In the article we also include an exemplary statistical analysis of trends, performed based on historical tick data from a six-year period (2013-2019), for AUD/NZD currency pair. In order to execute the research a dedicated software was created in MQL4 and C++.
Author Michał Stasiak (WZ / KIiN)
Michał Stasiak,,
- Department of Investment and Real Estate
Publication size in sheets0.5
Book Houda Michal, Remeš Radim (eds.): 37th International Conference Mathematical Methods in Economics MME 2019 : Conference Proceedings, 2019, University of South Bohemia in České Budějovice, Faculty of Economics, ISBN 978-80-7394-760-6, 598 p.
Keywords in Polishrynek walutowy, ekonometria wysokich częstotliwości, analiza techniczna, analiza trendum modelowanie kursuów watlutowych, wspomaganie decyzji inwestycyjnych
Keywords in Englishforeign exchange market, high frequency econometric, technical analysis, trend analysis, modelling of currency exchange rates, currency market investment decision support
Languageen angielski
Score (nominal)5
Score sourcepublisherList
ScoreMinisterial score = 5.0, 30-01-2020, ChapterFromConference
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