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Detection of Repetitive Forex Chart Patterns

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Advances in Swarm Intelligence (ICSI 2017)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 10386))

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Abstract

Throughout the years, numerous methods have been proposed for FOREX trading analysis and forecasting. As analysts/traders prefer to work with historical trading data, technical analysis based methods are often used. This paper presents an in-depth examination of technical analysis methods with an emphasis on charting/pattern-based analysis. Our findings indicate how to overcome the subjectivity often associated with identification and extraction of patterns within FOREX historical data. Based on historical facts that FOREX chart patterns repeat over time, the proposed method improves the approach towards identification of chart patterns as well as prediction of their recurrence regardless of the time warping effect affecting their formation.

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References

  1. King, M.R., Mallo, C.: A user’s guide to the Triennial Central Bank Survey of foreign exchange market activity. BIS Q. Rev., 71–83 (2010)

    Google Scholar 

  2. Bank of International Settlements: Triennial Central Bank Survey - Foreign Exchange Turnover in April 2013: Preliminary Global Result (2013)

    Google Scholar 

  3. Schulmeister, S.: Components of the profitability of technical currency trading. Appl. Financ. Econ. 18(11), 917–930 (2008)

    Article  Google Scholar 

  4. Neely, C.J., Weller, P.A.: Technical analysis in the foreign exchange market. Federal Reserve Bank of St. Louis Working Paper Series 2011-001B (2011)

    Google Scholar 

  5. Hsu, P.H., Taylor, M.P., Wang, Z.: Technical trading: is it still beating the foreign exchange market? J. Int. Econ. 102, 188–208 (2016)

    Article  Google Scholar 

  6. Bagheri, A., Peyhani, H.M., Akbari, M.: Financial forecasting using ANFIS networks with quantum-behaved particle swarm optimization. Expert Syst. Appl. 41(14), 6235–6250 (2014)

    Article  Google Scholar 

  7. Gerlein, E.A., McGinnity, M., Belatreche, A., Coleman, S.: Evaluating machine learning classification for financial trading: an empirical approach. Expert Syst. Appl. 54, 193–207 (2016)

    Article  Google Scholar 

  8. Czekalski, P., Niezabitowski, M., Styblinski, R.: ANN for FOREX forecasting and trading. In: 20th International Conference on Control Systems and Computer Science (CSCS 2015), pp. 322–328 (2015)

    Google Scholar 

  9. Ozturk, M., Toroslu, I.H., Fidan, G.: Heuristic based trading system on Forex data using technical indicator rules. Appl. Soft Comput. 43, 170–186 (2016)

    Article  Google Scholar 

  10. Forex indicators: The best guide to indicator’s world. http://forex-indicators.net/list

  11. Gallo, C.: The forex market in practice: a computing approach for automated trading strategies. Int. J. Econ. Manag. Sci. 3(169), 1–9 (2014)

    MathSciNet  Google Scholar 

  12. Bulkowski, T.N.: Encyclopedia of Chart Patterns, 2nd edn. Wiley, New York (2005)

    Google Scholar 

  13. Ito, T., Hashimoto, Y.: Intraday seasonality in activities of the foreign exchange markets: evidence from the electronic broking system. J. Jpn. Int. Econ. 20(4), 637–664 (2006)

    Article  Google Scholar 

  14. Person, J.L.: A Complete Guide to Technical Trading Tactics: How to Profit Using Pivot Points, Candlesticks & Other Indicators. Wiley, New York (2004)

    Google Scholar 

  15. Talebi, H., Hoang, W., Gavrilova, M.L.: Multi-scale foreign exchange rates ensemble for classification of trends in forex market. Procedia Comput. Sci. 29, 2065–2075 (2014)

    Article  Google Scholar 

  16. Muggeo, V.M.R.: Estimating regression models with unknown break-points. Stat. Med. 22(19), 3055–3071 (2003)

    Article  Google Scholar 

  17. Wood, S.N.: Minimizing model fitting objectives that contain spurious local minima by bootstrap restarting. Biometrics 57(1), 240–244 (2001)

    Article  MathSciNet  MATH  Google Scholar 

  18. HistData. http://www.histdata.com/download-free-forex-data

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Author information

Authors and Affiliations

  1. Department of Computing and Information Systems, Sunway University, Bandar Sunway, Malaysia

    Yoke Leng Yong, David C. L. Ngo & Yunli Lee

Authors
  1. Yoke Leng Yong
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  2. David C. L. Ngo
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  3. Yunli Lee
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Corresponding author

Correspondence to Yoke Leng Yong .

Editor information

Editors and Affiliations

  1. Peking University, Beijing, China

    Ying Tan

  2. Kyushu University, Fukuoka, Japan

    Hideyuki Takagi

  3. Southern University of Science and Technology, Shenzhen, China

    Yuhui Shi

  4. Shenzhen University, Shenzhen, China

    Ben Niu

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© 2017 Springer International Publishing AG

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Yong, Y.L., Ngo, D.C.L., Lee, Y. (2017). Detection of Repetitive Forex Chart Patterns. In: Tan, Y., Takagi, H., Shi, Y., Niu, B. (eds) Advances in Swarm Intelligence. ICSI 2017. Lecture Notes in Computer Science(), vol 10386. Springer, Cham. https://doi.org/10.1007/978-3-319-61833-3_42

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  • DOI: https://doi.org/10.1007/978-3-319-61833-3_42

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-61832-6

  • Online ISBN: 978-3-319-61833-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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