IDEAS home Printed from https://ideas.repec.org/a/eee/pacfin/v26y2014icp65-78.html
   My bibliography  Save this article

The profitability of candlestick charting in the Taiwan stock market

Author

Listed:
  • Lu, Tsung-Hsun

Abstract

The purpose of this study is to examine the predictive power of candlestick charting by using the daily data for the Taiwan stocks for the period from 4 January 1992 to 31 December 2009. The main contribution of this paper is devising a four-price-level approach to categorize the single-line patterns produced by candlestick charting in a systematic manner. The findings reveal that four patterns are profitable for the Taiwan stock market after transaction costs, and a bootstrap analysis, out-of-sample, and several sub-samples are examined to confirm the robustness of the results.

Suggested Citation

  • Lu, Tsung-Hsun, 2014. "The profitability of candlestick charting in the Taiwan stock market," Pacific-Basin Finance Journal, Elsevier, vol. 26(C), pages 65-78.
  • Handle: RePEc:eee:pacfin:v:26:y:2014:i:c:p:65-78
    DOI: 10.1016/j.pacfin.2013.10.006
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0927538X13000735
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.pacfin.2013.10.006?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Hendrik Bessembinder & Kalok Chan, 1998. "Market Efficiency and the Returns to Technical Analysis," Financial Management, Financial Management Association, vol. 27(2), Summer.
    2. Ryan Sullivan & Allan Timmermann & Halbert White, 1999. "Data‐Snooping, Technical Trading Rule Performance, and the Bootstrap," Journal of Finance, American Finance Association, vol. 54(5), pages 1647-1691, October.
    3. Sullivan, Ryan & Timmermann, Allan & White, Halbert, 2003. "Forecast evaluation with shared data sets," International Journal of Forecasting, Elsevier, vol. 19(2), pages 217-227.
    4. 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.
    5. Mark J Ready, 2002. "Profits from Technical Trading Rules," Financial Management, Financial Management Association, vol. 31(3), Fall.
    6. Lo, Andrew W & MacKinlay, A Craig, 1990. "When Are Contrarian Profits Due to Stock Market Overreaction?," The Review of Financial Studies, Society for Financial Studies, vol. 3(2), pages 175-205.
    7. Bloomfield, Robert & Hales, Jeffrey, 2002. "Predicting the next step of a random walk: experimental evidence of regime-shifting beliefs," Journal of Financial Economics, Elsevier, vol. 65(3), pages 397-414, September.
    8. Treynor, Jack L & Ferguson, Robert, 1985. "In Defense of Technical Analysis," Journal of Finance, American Finance Association, vol. 40(3), pages 757-773, July.
    9. Chou, Pin-Huang & Wei, K.C. John & Chung, Huimin, 2007. "Sources of contrarian profits in the Japanese stock market," Journal of Empirical Finance, Elsevier, vol. 14(3), pages 261-286, June.
    10. Ito, Akitoshi, 1999. "Profits on technical trading rules and time-varying expected returns: evidence from Pacific-Basin equity markets," Pacific-Basin Finance Journal, Elsevier, vol. 7(3-4), pages 283-330, August.
    11. Olson, Dennis, 2004. "Have trading rule profits in the currency markets declined over time?," Journal of Banking & Finance, Elsevier, vol. 28(1), pages 85-105, January.
    12. 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.
    13. Robert J. Bloomfield & William B. Tayler & Flora (Hailan) Zhou, 2009. "Momentum, Reversal, and Uninformed Traders in Laboratory Markets," Journal of Finance, American Finance Association, vol. 64(6), pages 2535-2558, December.
    14. De Long, J Bradford, et al, 1990. "Positive Feedback Investment Strategies and Destabilizing Rational Speculation," Journal of Finance, American Finance Association, vol. 45(2), pages 379-395, June.
    15. De Bondt, Werner F M & Thaler, Richard, 1985. "Does the Stock Market Overreact?," Journal of Finance, American Finance Association, vol. 40(3), pages 793-805, July.
    16. Fung, Alexander Kwok-Wah & Lam, Kin & Lam, Ka-Ming, 2010. "Do the prices of stock index futures in Asia overreact to U.S. market returns?," Journal of Empirical Finance, Elsevier, vol. 17(3), pages 428-440, June.
    17. Andrew W. Lo & Harry Mamaysky & Jiang Wang, 2000. "Foundations of Technical Analysis: Computational Algorithms, Statistical Inference, and Empirical Implementation," Journal of Finance, American Finance Association, vol. 55(4), pages 1705-1765, August.
    18. Kwok-Wah Fung, Alexander & Lam, Kin, 2004. "Overreaction of index futures in Hong Kong," Journal of Empirical Finance, Elsevier, vol. 11(3), pages 331-351, June.
    19. 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.
    20. Jegadeesh, Narasimhan & Titman, Sheridan, 1995. "Overreaction, Delayed Reaction, and Contrarian Profits," The Review of Financial Studies, Society for Financial Studies, vol. 8(4), pages 973-993.
    21. Blume, Lawrence & Easley, David & O'Hara, Maureen, 1994. "Market Statistics and Technical Analysis: The Role of Volume," Journal of Finance, American Finance Association, vol. 49(1), pages 153-181, March.
    22. Fama, Eugene F & French, Kenneth R, 1996. "Multifactor Explanations of Asset Pricing Anomalies," Journal of Finance, American Finance Association, vol. 51(1), pages 55-84, March.
    23. Lakonishok, Josef & Shleifer, Andrei & Vishny, Robert W, 1994. "Contrarian Investment, Extrapolation, and Risk," Journal of Finance, American Finance Association, vol. 49(5), pages 1541-1578, December.
    24. Brock, William & Lakonishok, Josef & LeBaron, Blake, 1992. "Simple Technical Trading Rules and the Stochastic Properties of Stock Returns," Journal of Finance, American Finance Association, vol. 47(5), pages 1731-1764, December.
    25. Lu, Tsung-Hsun & Shiu, Yung-Ming & Liu, Tsung-Chi, 2012. "Profitable candlestick trading strategies—The evidence from a new perspective," Review of Financial Economics, Elsevier, vol. 21(2), pages 63-68.
    26. Sweeney, Richard J, 1986. "Beating the Foreign Exchange Market," Journal of Finance, American Finance Association, vol. 41(1), pages 163-182, March.
    27. Tsung-Hsun Lu & Yung-Ming Shiu, 2012. "Tests for Two-Day Candlestick Patterns in the Emerging Equity Market of Taiwan," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 48(0), pages 41-57, January.
    28. Levy, Robert A, 1971. "The Predicitive Significance of Five-Point Chart Patterns," The Journal of Business, University of Chicago Press, vol. 44(3), pages 316-323, July.
    29. Ratner, Mitchell & Leal, Ricardo P. C., 1999. "Tests of technical trading strategies in the emerging equity markets of Latin America and Asia," Journal of Banking & Finance, Elsevier, vol. 23(12), pages 1887-1905, December.
    30. repec:bla:jfinan:v:55:y:2000:i:4:p:1705-1770 is not listed on IDEAS
    31. Goldbaum, David, 1999. "A nonparametric examination of market information: application to technical trading rules," Journal of Empirical Finance, Elsevier, vol. 6(1), pages 59-85, January.
    32. Day, Theodore E. & Wang, Pingying, 2002. "Dividends, nonsynchronous prices, and the returns from trading the Dow Jones Industrial Average," Journal of Empirical Finance, Elsevier, vol. 9(4), pages 431-454, November.
    33. G. Caginalp & H. Laurent, 1998. "The predictive power of price patterns," Applied Mathematical Finance, Taylor & Francis Journals, vol. 5(3-4), pages 181-205.
    34. Po-Hsuan Hsu & Chung-Ming Kuan, 2005. "Reexamining the Profitability of Technical Analysis with Data Snooping Checks," Journal of Financial Econometrics, Oxford University Press, vol. 3(4), pages 606-628.
    35. Horton, Marshall J., 2009. "Stars, crows, and doji: The use of candlesticks in stock selection," The Quarterly Review of Economics and Finance, Elsevier, vol. 49(2), pages 283-294, May.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Lu, Tsung-Hsun & Chen, Yi-Chi & Hsu, Yu-Chin, 2015. "Trend definition or holding strategy: What determines the profitability of candlestick charting?," Journal of Banking & Finance, Elsevier, vol. 61(C), pages 172-183.
    2. Chiang, Mi-Hsiu & Chiu, Hsin-Yu & Kuo, Wei-Yu, 2021. "Predictive ability of similarity-based futures trading strategies," Pacific-Basin Finance Journal, Elsevier, vol. 68(C).
    3. Shangkun Deng & Zhihao Su & Yanmei Ren & Haoran Yu & Yingke Zhu & Chenyang Wei, 2022. "Can Japanese Candlestick Patterns be Profitable on the Component Stocks of the SSE50 Index?," SAGE Open, , vol. 12(3), pages 21582440221, August.
    4. Piyapas Tharavanij & Vasan Siraprapasiri & Kittichai Rajchamaha, 2017. "Profitability of Candlestick Charting Patterns in the Stock Exchange of Thailand," SAGE Open, , vol. 7(4), pages 21582440177, October.
    5. U, JuHyok & Lu, PengYu & Kim, ChungSong & Ryu, UnSok & Pak, KyongSok, 2020. "A new LSTM based reversal point prediction method using upward/downward reversal point feature sets," Chaos, Solitons & Fractals, Elsevier, vol. 132(C).
    6. Tsung-Hsun Lu & Yung-Ming Shiu, 2016. "Can 1-day candlestick patterns be profitable on the 30 component stocks of the DJIA?," Applied Economics, Taylor & Francis Journals, vol. 48(35), pages 3345-3354, July.
    7. Ni, Yensen & Cheng, Yirung & Huang, Paoyu & Day, Min-Yuh, 2018. "Trading strategies in terms of continuous rising (falling) prices or continuous bullish (bearish) candlesticks emitted," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 501(C), pages 188-204.
    8. Marko Pov{z}enel & Dejan Lavbiv{c}, 2019. "Discovering Language of the Stocks," Papers 1902.08684, arXiv.org.
    9. Shangkun Deng & Haoran Yu & Chenyang Wei & Tianxiang Yang & Shimada Tatsuro, 2021. "The profitability of Ichimoku Kinkohyo based trading rules in stock markets and FX markets," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(4), pages 5321-5336, October.
    10. Alhashel, Bader S. & Almudhaf, Fahad W. & Hansz, J. Andrew, 2018. "Can technical analysis generate superior returns in securitized property markets? Evidence from East Asia markets," Pacific-Basin Finance Journal, Elsevier, vol. 47(C), pages 92-108.
    11. Chiu, Hsin-Yu & Chiang, Mi-Hsiu & Kuo, Wei-Yu, 2018. "Predicative Ability of Similarity-based Futures Trading Strategies," IRTG 1792 Discussion Papers 2018-045, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    12. Zhu, Min & Atri, Said & Yegen, Eyub, 2016. "Are candlestick trading strategies effective in certain stocks with distinct features?," Pacific-Basin Finance Journal, Elsevier, vol. 37(C), pages 116-127.
    13. Tseng, Yi-Heng & Chen, Shu-Heng, 2015. "Limit order book transparency and order aggressiveness at the closing call: Lessons from the TWSE 2012 new information disclosure mechanism," Pacific-Basin Finance Journal, Elsevier, vol. 35(PA), pages 241-272.
    14. Chen, Shi & Bao, Si & Zhou, Yu, 2016. "The predictive power of Japanese candlestick charting in Chinese stock market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 457(C), pages 148-165.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Tsung-Hsun Lu & Yung-Ming Shiu, 2016. "Can 1-day candlestick patterns be profitable on the 30 component stocks of the DJIA?," Applied Economics, Taylor & Francis Journals, vol. 48(35), pages 3345-3354, July.
    2. Osman Kilic & Joseph M. Marks & Kiseok Nam, 2022. "Predictable asset price dynamics, risk-return tradeoff, and investor behavior," Review of Quantitative Finance and Accounting, Springer, vol. 59(2), pages 749-791, August.
    3. Chen, Shi & Bao, Si & Zhou, Yu, 2016. "The predictive power of Japanese candlestick charting in Chinese stock market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 457(C), pages 148-165.
    4. Lu, Tsung-Hsun & Chen, Yi-Chi & Hsu, Yu-Chin, 2015. "Trend definition or holding strategy: What determines the profitability of candlestick charting?," Journal of Banking & Finance, Elsevier, vol. 61(C), pages 172-183.
    5. 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.
    6. Shynkevich, Andrei, 2012. "Performance of technical analysis in growth and small cap segments of the US equity market," Journal of Banking & Finance, Elsevier, vol. 36(1), pages 193-208.
    7. Ülkü, Numan & Prodan, Eugeniu, 2013. "Drivers of technical trend-following rules' profitability in world stock markets," International Review of Financial Analysis, Elsevier, vol. 30(C), pages 214-229.
    8. Strobel, Marcus & Auer, Benjamin R., 2018. "Does the predictive power of variable moving average rules vanish over time and can we explain such tendencies?," International Review of Economics & Finance, Elsevier, vol. 53(C), pages 168-184.
    9. Shynkevich, Andrei, 2013. "Time-series momentum as an intra- and inter-industry effect: Implications for market efficiency," Journal of Economics and Business, Elsevier, vol. 69(C), pages 64-85.
    10. Lukas Menkhoff & Mark P. Taylor, 2007. "The Obstinate Passion of Foreign Exchange Professionals: Technical Analysis," Journal of Economic Literature, American Economic Association, vol. 45(4), pages 936-972, December.
    11. Hsu, Po-Hsuan & Hsu, Yu-Chin & Kuan, Chung-Ming, 2010. "Testing the predictive ability of technical analysis using a new stepwise test without data snooping bias," Journal of Empirical Finance, Elsevier, vol. 17(3), pages 471-484, June.
    12. Hung, Chiayu & Lai, Hung-Neng, 2022. "Information asymmetry and the profitability of technical analysis," Journal of Banking & Finance, Elsevier, vol. 134(C).
    13. Alhashel, Bader S. & Almudhaf, Fahad W. & Hansz, J. Andrew, 2018. "Can technical analysis generate superior returns in securitized property markets? Evidence from East Asia markets," Pacific-Basin Finance Journal, Elsevier, vol. 47(C), pages 92-108.
    14. Fernando Rubio, 2005. "Eficiencia De Mercado, Administracion De Carteras De Fondos Y Behavioural Finance," Finance 0503028, University Library of Munich, Germany, revised 23 Jul 2005.
    15. Chiang, Mi-Hsiu & Chiu, Hsin-Yu & Kuo, Wei-Yu, 2021. "Predictive ability of similarity-based futures trading strategies," Pacific-Basin Finance Journal, Elsevier, vol. 68(C).
    16. Ślepaczuk Robert & Sakowski Paweł & Zakrzewski Grzegorz, 2018. "Investment Strategies that Beat the Market. What Can We Squeeze from the Market?," Financial Internet Quarterly (formerly e-Finanse), Sciendo, vol. 14(4), pages 36-55, December.
    17. Paskalis Glabadanidis, 2015. "Market Timing With Moving Averages," International Review of Finance, International Review of Finance Ltd., vol. 15(3), pages 387-425, September.
    18. Hsu, Po-Hsuan & Taylor, Mark P. & Wang, Zigan, 2016. "Technical trading: Is it still beating the foreign exchange market?," Journal of International Economics, Elsevier, vol. 102(C), pages 188-208.
    19. Friesen, Geoffrey C. & Weller, Paul A. & Dunham, Lee M., 2009. "Price trends and patterns in technical analysis: A theoretical and empirical examination," Journal of Banking & Finance, Elsevier, vol. 33(6), pages 1089-1100, June.
    20. Taylor, Mark & Hsu, Po-Hsuan, 2014. "Forty Years, Thirty Currencies and 21,000 Trading Rules: A Large-scale, Data-Snooping Robust Analysis of Technical Trading in t," CEPR Discussion Papers 10018, C.E.P.R. Discussion Papers.

    More about this item

    Keywords

    Technical analysis; Candlestick pattern; Behavioral finance; Bootstrap methodology;
    All these keywords.

    JEL classification:

    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:pacfin:v:26:y:2014:i:c:p:65-78. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/pacfin .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.