Identification of the head-and-shoulders technical analysis pattern with neural networks

Book chapter

Zapranis, A. and Tsinaslanidis, P. 2010. Identification of the head-and-shoulders technical analysis pattern with neural networks. in: Diamantaras, K., Duch, W. and Iliadis, L. (ed.) Artificial Neural Networks - ICANN 2010 Springer.
AuthorsZapranis, A. and Tsinaslanidis, P.
EditorsDiamantaras, K., Duch, W. and Iliadis, L.
Abstract

In this paper we present a novel approach for identifying the head-and-shoulders technical analysis pattern based on neural networks. For training the network we use actual patterns that were identified in stochastically simulated price series by means of a rule-based algorithm. Then the patterns are being converted to binary images, in a manner similar to the one used in hand-written character and digit recognition. Our approach is tested on new simulated price series using a rolling window of variable size. The results are very promising with an overall correct classification rate of 97.1%.

Year2010
Book titleArtificial Neural Networks - ICANN 2010
PublisherSpringer
Output statusPublished
SeriesLecture Notes in Computer Science
ISBN9783642158247
Publication dates
Print2010
Publication process dates
Deposited16 Sep 2014
Digital Object Identifier (DOI)https://doi.org/10.1007/978-3-642-15825-4_17
Journal citation6354, pp. 130-136
Permalink -

https://repository.canterbury.ac.uk/item/871w5/identification-of-the-head-and-shoulders-technical-analysis-pattern-with-neural-networks

  • 91
    total views
  • 0
    total downloads
  • 1
    views this month
  • 0
    downloads this month

Export as

Related outputs

A surrogate similarity measure for the mean-variance frontier optimization problem under bound and cardinality constraints
Guijarro, F. and Tsinaslanidis, P. 2019. A surrogate similarity measure for the mean-variance frontier optimization problem under bound and cardinality constraints. Journal of the Operational Research Society. https://doi.org/10.1080/01605682.2019.1657367
Subsequence dynamic time warping for charting: bullish and bearish class predictions for NYSE stocks
Tsinaslanidis, P. 2018. Subsequence dynamic time warping for charting: bullish and bearish class predictions for NYSE stocks. Expert Systems with Applications. 94, pp. 193-204. https://doi.org/10.1016/j.eswa.2017.10.055
Technical analysis for algorithmic pattern recognition
Tsinaslanidis, P. and Zapranis, A. 2016. Technical analysis for algorithmic pattern recognition. Springer.
Dynamic time warping as a similarity measure: applications in finance
Tsinaslanidis, P., Alexandridis, A., Zapranis, A. and Livanis, E. 2014. Dynamic time warping as a similarity measure: applications in finance.
Head and shoulders pattern recognition in stochastic processes
Tsinaslanidis, P. and Zapranis, A. 2008. Head and shoulders pattern recognition in stochastic processes.
An examination of the head and shoulders technical pattern; A support of the technical analysis’s subjective nature
Zapranis, A. and Tsinaslanidis, P. 2009. An examination of the head and shoulders technical pattern; A support of the technical analysis’s subjective nature.
A behavioral view of the head-and-shoulders technical analysis pattern
Zapranis, A. and Tsinaslanidis, P. 2010. A behavioral view of the head-and-shoulders technical analysis pattern.
Testing the generalised efficacy of technical analysis with bootstrapped aggregated regression trees
Zapranis, A. and Tsinaslanidis, P. 2012. Testing the generalised efficacy of technical analysis with bootstrapped aggregated regression trees.
Charting and weak-form market efficiency test: an empirical study on NASDAQ and NYSE components
Zapranis, A. and Tsinaslanidis, P. 2012. Charting and weak-form market efficiency test: an empirical study on NASDAQ and NYSE components. in: Essays in Honor of Prof. Dimitrios Papadopoulos Thessaloniki, Greece University of Macedonia.
A comprehensive review of hedge fund investment and trading strategies
Zapranis, A. and Tsinaslanidis, P. 2010. A comprehensive review of hedge fund investment and trading strategies. in: Essays in Honor of Late Professor J. Vartholomeos University of Piraeus. pp. 289-322
A novel, rule-based technical pattern identification mechanism: identifying and evaluating saucers and resistant levels in the US stock market
Zapranis, A. and Tsinaslanidis, P. 2012. A novel, rule-based technical pattern identification mechanism: identifying and evaluating saucers and resistant levels in the US stock market. Expert Systems with Applications. 39 (7), pp. 6301-6308. https://doi.org/10.1016/j.eswa.2011.11.079
Identifying and evaluating horizontal support and resistance levels: an empirical study on US stock markets
Zapranis, A. and Tsinaslanidis, P. 2012. Identifying and evaluating horizontal support and resistance levels: an empirical study on US stock markets. Applied Financial Economics. 22 (19), pp. 1571-1585. https://doi.org/10.1080/09603107.2012.663469
Business failure prediction using neural networks and wavelet neural networks
Alexandridis, A., Zapranis, A., Livanis, E. and Tsinaslanidis, P. 2013. Business failure prediction using neural networks and wavelet neural networks.
A prediction scheme using perceptually important points and dynamic time warping
Tsinaslanidis, P. and Kugiumtzis, D. 2014. A prediction scheme using perceptually important points and dynamic time warping. Expert Systems with Applications. 41 (15), pp. 6848-6860. https://doi.org/10.1016/j.eswa.2014.04.028