The application of the self-organizing map, the k-means algorithm and the multi-layer perceptron to the detection of technical trading patterns

J P  Marney; Heather Tarbert; Jos Koetsier; Marco G D  Guidi

doi:10.1080/09603100701367385

The application of the self-organizing map, the k-means algorithm and the multi-layer perceptron to the detection of technical trading patterns

J P Marney, Heather Tarbert, Jos Koetsier, Marco G D Guidi

School of Business and Creative Industries

Research output: Contribution to journal › Article

Abstract

A number of neural network techniques, namely multi-layer perceptron, k-means algorithm and the self-organizing map are applied to the detection of technical trading patterns within stock markets. We do not find exploitable information content and it is concluded that there are no significant patterns in any of the data analysed.

Original language	English
Pages (from-to)	1009-1019
Journal	Applied Financial Economics
Volume	18
Issue number	12
DOIs	https://doi.org/10.1080/09603100701367385
Publication status	Published - 2008

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10.1080/09603100701367385

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title = "The application of the self-organizing map, the k-means algorithm and the multi-layer perceptron to the detection of technical trading patterns",

abstract = "A number of neural network techniques, namely multi-layer perceptron, k-means algorithm and the self-organizing map are applied to the detection of technical trading patterns within stock markets. We do not find exploitable information content and it is concluded that there are no significant patterns in any of the data analysed.",

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The application of the self-organizing map, the k-means algorithm and the multi-layer perceptron to the detection of technical trading patterns

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