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Licensed Unlicensed Requires Authentication Published by De Gruyter August 18, 2017

A new recognition algorithm for “head-and-shoulders” price patterns

  • Terence Tai-Leung Chong EMAIL logo and Ka-Ho Poon

Abstract

Savin et al. [Savin, G., P. Weller, and J. Zvingelis. 2007. “The Predictive Power of “Head-and-Shoulders” Price Patterns in the US Stock Market.” Journal of Financial Econometrics 5: 243–265.] and Lo et al. [Lo, A. W., H. Mamaysky, and J. Wang. 2000. “Foundations of Technical Analysis: Computational Algorithms, Statistical Inference, and Empirical Implementation.” Journal of Finance 55: 1705–1765.] analysed the predictive power of head-and-shoulders (HS) patterns in the U.S. stock market. The algorithms in both studies ignored the relative position of the HS pattern in a price trend. In this paper, a filter that removes invalid HS patterns is proposed. It is found that the risk-adjusted excess returns for the HST pattern generally improve through the use of our filter.

JEL Classification: G02; G14; G17

Acknowledgments

We would like to thank Hugo Ip, Sunny Kwong and Julan Du for their helpful comments. We would also like to thank Min Chen, Mandy Cheung and Margaret Loo for their able research assistance. Any remaining errors are ours.

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Supplemental Material

The online version of this article offers supplementary material (DOI: https://doi.org/10.1515/snde-2015-0066).


Published Online: 2017-8-18

©2017 Walter de Gruyter GmbH, Berlin/Boston

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