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Do Technical Analysts Outperform Novice Traders: Experimental Evidence

Author

Listed:
  • Kim man Lui

    (Department of Computing, The Hong Kong Polytechnic University)

  • Terence T. L. Chong

    (Dept of Economics, Chinese Univ of Hong Kong and Dept of Int''l Economics and Trade, Nanjing Univ)

Abstract
Previous studies on technical analysis mostly report the profitability of specific trading rules for a given set of historical data. In this paper, we use the human trader experiment approach to compare the performance of experienced and novice traders. It is found that traders who are more knowledgeable on technical analysis significantly outperform those who are less knowledgeable.

Suggested Citation

  • Kim man Lui & Terence T. L. Chong, 2013. "Do Technical Analysts Outperform Novice Traders: Experimental Evidence," Economics Bulletin, AccessEcon, vol. 33(4), pages 3080-3087.
    • Handle: RePEc:ebl:ecbull:eb-13-00765
    as

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    File URL: http://www.accessecon.com/Pubs/EB/2013/Volume33/EB-13-V33-I4-P287.pdf
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    References listed on IDEAS

    as
    1. Chong, Terence Tai-Leung & Lam, Tau-Hing & Yan, Isabel Kit-Ming, 2012. "Is the Chinese stock market really inefficient?," China Economic Review, Elsevier, vol. 23(1), pages 122-137.
    2. Chong, Terence Tai-Leung & Ip, Hugo Tak-Sang, 2009. "Do momentum-based strategies work in emerging currency markets?," Pacific-Basin Finance Journal, Elsevier, vol. 17(4), pages 479-493, September.
    3. Cheol‐Ho Park & Scott H. Irwin, 2007. "What Do We Know About The Profitability Of Technical Analysis?," Journal of Economic Surveys, Wiley Blackwell, vol. 21(4), pages 786-826, September.
    4. Ben Marshall & Martin Young & Rochester Cahan, 2008. "Are candlestick technical trading strategies profitable in the Japanese equity market?," Review of Quantitative Finance and Accounting, Springer, vol. 31(2), pages 191-207, August.
    5. Anderson, John A. & Faff, Robert W., 2008. "Point and Figure charting: A computational methodology and trading rule performance in the S&P 500 futures market," International Review of Financial Analysis, Elsevier, vol. 17(1), pages 198-217.
    6. Fama, Eugene F, 1970. "Efficient Capital Markets: A Review of Theory and Empirical Work," Journal of Finance, American Finance Association, vol. 25(2), pages 383-417, May.
    7. G. Caginalp & G. Constantine, 1995. "Statistical inference and modelling of momentum in stock prices," Applied Mathematical Finance, Taylor & Francis Journals, vol. 2(4), pages 225-242.
    8. Terence Tai-Leung Chong & Wing-Kam Ng, 2008. "Technical analysis and the London stock exchange: testing the MACD and RSI rules using the FT30," Applied Economics Letters, Taylor & Francis Journals, vol. 15(14), pages 1111-1114.
    9. Marshall, Ben R. & Young, Martin R. & Rose, Lawrence C., 2006. "Candlestick technical trading strategies: Can they create value for investors?," Journal of Banking & Finance, Elsevier, vol. 30(8), pages 2303-2323, August.
    10. Terence Tai-Leung Chong & Tau-Hing Lam & Melvin J. Hinich, 2009. "Are Nonlinear Trading Rules Profitable In The Chinese Stock Market?," Annals of Financial Economics (AFE), World Scientific Publishing Co. Pte. Ltd., vol. 5(01), pages 1-20.
    Full references (including those not matched with items on IDEAS)

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    Cited by:

    1. Terence Tai-Leung Chong & Wing-Kam Ng & Venus Khim-Sen Liew, 2014. "Revisiting the Performance of MACD and RSI Oscillators," JRFM, MDPI, vol. 7(1), pages 1-12, February.
    2. Nguyen Tien Zung, 2017. "Second order stochastic differential models for financial markets," Papers 1707.05419, arXiv.org.

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    More about this item

    Keywords

    Technical analysis; human trader experiments; candle sticks;
    All these keywords.

    JEL classification:

    • G1 - Financial Economics - - General Financial Markets
    • C9 - Mathematical and Quantitative Methods - - Design of Experiments

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