Publikace detail

Automatic head and shoulders pattern recognition using nonlinear statistical modelling

Autoři: Heckenbergerová Jana | Marek Jaroslav | Mejznar Jakub

Rok: 2013

Druh publikace: ostatní - článek ve sborníku

Název zdroje: APLIMAT 2013, 12th Conference on Applied Mathematics, Book of Abstracts

Název nakladatele: Slovenská technická univezita v Bratislave

Místo vydání: Bratislava

Strana od-do: 58

Tituly:

Jazyk	Název	Abstrakt	Klíčová slova
eng	Automatic head and shoulders pattern recognition using nonlinear statistical modelling	Chart Pattern recognition is one of the keystone of Technical Analysis, discipline that concentrates all methods of market development evaluation. Graphical formations such as Head and Shoulders, Flag or Triangle are usually detected only visually by experts long after their appearance. The aim of presented contribution is introduction of new automatic algorithm for Head and Shoulders Pattern (HaSP) detection. The algorithm is based on nonlinear function approximation and statistical estimation of unknown parameters. Whole procedure is tested in Case Study consisting long time series of Dow Jones average indexes. In the end, the successfulness of different market strategies is tested by statistical analysis of percentage profit. Results show that pattern appearance does not have significant effect on prices development.	Technical analysis, Chart patterns, Market Strategies, Nonlinear approximation, Regression model, Linearization, Index of determination.

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