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Mathematical Problems in Engineering
Volume 2017 (2017), Article ID 3096917, 11 pages
https://doi.org/10.1155/2017/3096917
Research Article

K-Line Patterns’ Predictive Power Analysis Using the Methods of Similarity Match and Clustering

1College of Electronics and Information Engineering, Tongji University, Shanghai 200092, China
2Rabun Gap-Nacoochee School, Rabun Gap, GA 30568, USA
3Shanghai Baosight Software Co., Ltd., Shanghai 200092, China

Correspondence should be addressed to Lv Tao

Received 23 December 2016; Revised 31 March 2017; Accepted 5 April 2017; Published 22 May 2017

Academic Editor: Anna M. Gil-Lafuente

Copyright © 2017 Lv Tao et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Linked References

  1. J. Lin, S. Williamson, K. D. Borne et al., “Advances in machine learning & data mining for astronomy,” Pattern Recognition in Time Series, pp. 617–645, 2010. View at Google Scholar
  2. L. Lihui, T. Xiang, Y. Haidong et al., “Financial time series forecasting based on SVR,” Computer Engineering and Applications, vol. 41, no. 30, pp. 221–224, 2005. View at Google Scholar
  3. R. D. Edwards, J. Magee, and W. H. C. Bassetti, Technical Analysis of Stock Trends, CRC Press, Boca Raton, Fla, USA, 10th edition, 2012.
  4. S. Nison, Japanese Candlestick Charting Techniques: A Contemporary Guide to the Ancient Investment, Technique of the Far East, Institute of Finance, New York, NY, USA, 1991.
  5. B. R. Marshall, M. R. Young, and L. C. Rose, “Candlestick technical trading strategies: can they create value for investors?” Journal of Banking and Finance, vol. 30, no. 8, pp. 2303–2323, 2006. View at Publisher · View at Google Scholar · View at Scopus
  6. G. Caginalp and H. Laurent, “The predictive power of price patterns,” Applied Mathematical Finance, vol. 5, no. 3-4, pp. 181–205, 1998. View at Publisher · View at Google Scholar
  7. K. H. Lee and G. S. Jo, “Expert system for predicting stock market timing using a candlestick chart,” Expert Systems with Applications, vol. 16, no. 4, pp. 357–364, 1999. View at Publisher · View at Google Scholar · View at Scopus
  8. M. M. Goswami, C. K. Bhensdadia, and A. P. Ganatra, “Candlestick analysis based short term prediction of stock price fluctuation usingSOM-CBR,” in Proceedings of the 2009 IEEE International Advance Computing Conference (IACC '09), pp. 1448–1452, March 2009. View at Publisher · View at Google Scholar · View at Scopus
  9. T. H. Lu and J. Chen, Candlestick charting in European stock markets, no. 2, pp. 20–25, 2013.
  10. T. H. Lu and Y. M. Shiu, “Tests for two day candlestick patterns in the emerging equity market of Taiwan,” Emerging Markets Finance & Trade, vol. 48, no. 1, pp. 41–57, 2014. View at Google Scholar
  11. H. Li, W. W. Y. Ng, J. W. T. Lee, B. Sun, and D. S. Yeung, “Quantitative study on candlestick pattern for shenzhen stock market,” in Proceedings of the 2008 IEEE International Conference on Systems, Man and Cybernetics, (SMC '08), pp. 54–59, October 2008. View at Publisher · View at Google Scholar · View at Scopus
  12. W. Xiao, W. W. Y. Ng, M. Firth et al., “L-GEM based MCS aided candlestick pattern investment strategy in the shenzhen stock market,” in Proceedings of the 2009 International Conference on Machine Learning and Cybernetics, pp. 243–248, July 2009. View at Publisher · View at Google Scholar · View at Scopus
  13. T. Kamo and C. Dagli, “Hybrid approach to the Japanese candlestick method for financial forecasting,” Expert Systems with Applications, vol. 36, no. 3, pp. 5023–5030, 2009. View at Publisher · View at Google Scholar · View at Scopus
  14. M. Jasemi, A. M. Kimiagari, and A. Memariani, “A modern neural network model to do stock market timing on the basis of the ancient investment technique of Japanese Candlestick,” Expert Systems with Applications, vol. 38, no. 4, pp. 3884–3890, 2011. View at Publisher · View at Google Scholar · View at Scopus
  15. S. Barak, J. H. Dahooie, and T. Tichý, “Wrapper ANFIS-ICA method to do stock market timing and feature selection on the basis of Japanese Candlestick,” Expert Systems with Applications, vol. 42, no. 23, pp. 9221–9235, 2015. View at Publisher · View at Google Scholar · View at Scopus
  16. J. H. Fock, C. Klein, and B. Zwergel, “Performance of candlestick analysis on intraday futures data,” The Journal of Derivatives, vol. 13, no. 1, pp. 28–40, 2005. View at Publisher · View at Google Scholar
  17. B. R. Marshall, M. R. Young, and R. Cahan, “Are candlestick technical trading strategies profitable in the Japanese equity market?” Review of Quantitative Finance and Accounting, vol. 31, no. 2, pp. 191–207, 2008. View at Publisher · View at Google Scholar · View at Scopus
  18. M. J. Horton, “Stars, crows, and doji: the use of candlesticks in stock selection,” Quarterly Review of Economics and Finance, vol. 49, no. 2, pp. 283–294, 2009. View at Publisher · View at Google Scholar · View at Scopus
  19. L. J. Chmielewski, M. Janowicz, and A. Orłowski, “Prediction of trend reversals in stock market by classification of Japanese candlesticks,” in Proceedings of the 9th International Conference on Computer Recognition Systems (CORES '15), vol. 403, pp. 641–647. View at Publisher · View at Google Scholar · View at Scopus
  20. C.-F. Tsai and Z.-Y. Quan, “Stock prediction by searching for similarities in candlestick charts,” ACM Transactions on Management Information Systems, vol. 5, no. 2, Article ID 2591672, 2014. View at Publisher · View at Google Scholar · View at Scopus
  21. L. Chmielewski, M. Janowicz, J. Kaleta, and A. Orłowski, “Pattern recognition in the Japanese candlesticks,” Advances in Intelligent Systems and Computing, vol. 342, pp. 227–234, 2015. View at Publisher · View at Google Scholar · View at Scopus
  22. G. L. Morris and R. Litchfield, Candlestick Charting Explained: Timeless Techniques for Trading Stocks and Futures, McGraw-Hill, New Yourk, NY, USA, 2nd edition, 2006.