Short Term Trading Strategy Based on Chart Pattern Recognition and Trend Trading in Nasdaq Biotechnology Stock Market

  • Saulius Masteika
Part of the Lecture Notes in Business Information Processing book series (LNBIP, volume 57)


The main task of this paper is to show the results of stock market trading strategy based on short term chart pattern. Proposed short term chart pattern is a trend following pattern and is relative to fractal formations and chaos theory. The proposed trading strategy consists of two steps: on the first step the stock screening algorithm is used to select volatile stocks in Nasdaq Biotechnology market; on the second step technical analysis and mathematical calculations for selected stocks are applied and profitability of strategy is calculated. The proposed trading strategy based on short term chart pattern was tested using historical data records from the USA Nasdaq Biotechnology market (2008-2010). The trading strategy applied in Biotechnology stock market had given higher returns if compared to the main USA stock market indexes (Dow Jones, S&P, Nasdaq).


Stock Market Price Change Trading Strategy Volatile Stock Market Trading Signal 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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  1. 1.
    Alan, N.: The complete guide to investing in short term trading: How to earn high rates of returns safely, p.288. Atlantic Publishing Company (FL) (2008)Google Scholar
  2. 2.
    Williams, B.: New trading dimensions, p. 288. John Wiley & Sons, New York (1998)Google Scholar
  3. 3.
    Williams, B.M., Williams, J.G.: Trading chaos: maximize profits with proven technical techniques, 2nd edn., p. 228. John Wiley & Sons, Inc., New Jersey (2004)Google Scholar
  4. 4.
    Masteika, S., Simutis, R.: Stock trading system based on formalized technical analysis and ranking technique. In: Alexandrov, V.N., van Albada, G.D., Sloot, P.M.A., Dongarra, J. (eds.) ICCS 2006. LNCS, vol. 3994, pp. 332–339. Springer, Heidelberg (2006)CrossRefGoogle Scholar
  5. 5.
    Ned, G.: Winning Edge trading: successful and profitable short and long term systems and strategies, p. 224. Wiley trading, Chichester (2009)Google Scholar
  6. 6.
    Turner, T.: Short-term trading in the new market, p. 384. St.Martin’s Griffin (2006)Google Scholar
  7. 7.
    Masteika, S.: Formalization and application of technical analysis indicators in securities markets, Doctoral Dissertation, Vilnius, p.147 (2007)Google Scholar
  8. 8.
    Achelis, S.B.: Technical Analysis from A to Z, 2nd edn., p. 380. McGraw-Hill, New York (2000)Google Scholar
  9. 9.
    DeBondt, W., Thaler, R.: Does the stock market overreact? Journal of Finance 40, 793–805 (1985)CrossRefGoogle Scholar
  10. 10.
    Chande Tushar, S.: Beyond Technical Analysis: How to develop and implement a winning trading system, 2nd edn., p. 336. Wiley, Chichester (2001)Google Scholar
  11. 11.
    Edwards, R.D., Magee, J.: Technical Analysis of Stock Trends, 7th edn., p. 792. John Magee, Inc. (1998)Google Scholar
  12. 12.
    Carr Thomas, K.: Trend trading for a living: learn skills and gain the confidence to trade for a living, p. 312. McGraw-Hill, New York (2007)Google Scholar
  13. 13.
    DeBondt, W., Thaler, R.: Further evidence on investor overreaction and stock market seasonality. Journal of Finance 42, 557–582 (1987)CrossRefGoogle Scholar
  14. 14.
    Hong, H., Stein, J.: A unified theory of underreaction, momentum trading, and overreaction in asset markets. The Journal of Finance LIV (6), 2143–2184 (1999)Google Scholar
  15. 15.
    Janssen, C., Langager, C., Murphy, C.: Technical analysis: chart patterns (February 25, 2010),

Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Saulius Masteika
    • 1
  1. 1.Faculty of HumanitiesVilnius UniversityKaunasLithuania

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