IDEAS home Printed from https://ideas.repec.org/a/kap/apfinm/v28y2021i4d10.1007_s10690-021-09337-5.html
   My bibliography  Save this article

Applying Technical Trading Rules to Beat Long-Term Investing: Evidence from Asian Markets

Author

Listed:
  • Thomas S. Coe
  • Kittipong Laosethakul

    (Sacred Heart University)

Abstract

We provide evidence that the use of technical trading rules provides traders the opportunity to generate profits from actively buying and selling individual stocks across Asian markets. We test the trading performance of three widely used technical trading strategies, the Arithmetic Moving Average, the Relative Strength Index, and the Stochastic Oscillator, as well as variations to each trading strategy. We compare the results of these trading rules to a long-term buy-and-hold strategy across 4822 stocks traded in 39 Asian countries. Our results, when applying a simple behavior intervention filter of only selling a position when a trade is profitable, show that these technical trading rules, on average, were able to outperform the buy-and-hold strategy for 66% of the stocks listed in our sample. Additionally, given any of the listed Asian stocks, we found that, on average, a trader could apply any technical trading strategy and have a greater than 50–50 chance of outperforming the buy-and hold strategy for that stock for 63% of all stocks.

Suggested Citation

  • Thomas S. Coe & Kittipong Laosethakul, 2021. "Applying Technical Trading Rules to Beat Long-Term Investing: Evidence from Asian Markets," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 28(4), pages 587-611, December.
    • Handle: RePEc:kap:apfinm:v:28:y:2021:i:4:d:10.1007_s10690-021-09337-5
    DOI: 10.1007/s10690-021-09337-5
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10690-021-09337-5
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s10690-021-09337-5?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. Wing-Keung Wong & Meher Manzur & Boon-Kiat Chew, 2003. "How rewarding is technical analysis? Evidence from Singapore stock market," Applied Financial Economics, Taylor & Francis Journals, vol. 13(7), pages 543-551.
    3. Shefrin, Hersh & Statman, Meir, 1985. "The Disposition to Sell Winners Too Early and Ride Losers Too Long: Theory and Evidence," Journal of Finance, American Finance Association, vol. 40(3), pages 777-790, July.
    4. Ki-Yeol Kwon & Richard Kish, 2002. "Technical trading strategies and return predictability: NYSE," Applied Financial Economics, Taylor & Francis Journals, vol. 12(9), pages 639-653.
    5. Poterba, James M. & Summers, Lawrence H., 1988. "Mean reversion in stock prices : Evidence and Implications," Journal of Financial Economics, Elsevier, vol. 22(1), pages 27-59, October.
    6. 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.
    7. 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.
    8. Tina Yu & Shu-Heng Chen, 2004. "Using Genetic Programming with Lambda Abstraction to Find Technical Trading Rules," Computing in Economics and Finance 2004 200, Society for Computational Economics.
    9. Bessembinder, Hendrik & Chan, Kalok, 1995. "The profitability of technical trading rules in the Asian stock markets," Pacific-Basin Finance Journal, Elsevier, vol. 3(2-3), pages 257-284, July.
    10. Salma Khand & Vivake Anand & Mohammad Nadeem Qureshi, 2020. "The Predictability and Profitability of Simple Moving Averages and Trading Range Breakout Rules in the Pakistan Stock Market," Review of Pacific Basin Financial Markets and Policies (RPBFMP), World Scientific Publishing Co. Pte. Ltd., vol. 23(01), pages 1-38, March.
    11. Yu, Hao & Nartea, Gilbert V. & Gan, Christopher & Yao, Lee J., 2013. "Predictive ability and profitability of simple technical trading rules: Recent evidence from Southeast Asian stock markets," International Review of Economics & Finance, Elsevier, vol. 25(C), pages 356-371.
    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. Day, Min-Yuh & Ni, Yensen, 2023. "Do clean energy indices outperform using contrarian strategies based on contrarian trading rules?," Energy, Elsevier, vol. 272(C).
    2. Chien-Liang Chiu & Paoyu Huang & Min-Yuh Day & Yensen Ni & Yuhsin Chen, 2024. "Mastery of “Monthly Effects”: Big Data Insights into Contrarian Strategies for DJI 30 and NDX 100 Stocks over a Two-Decade Period," Mathematics, MDPI, vol. 12(2), pages 1-22, January.
    3. Day, Min-Yuh & Ni, Yensen, 2023. "The profitability of seasonal trading timing: Insights from energy-related markets," Energy Economics, Elsevier, vol. 128(C).
    4. Ha Che-Ngoc & Nga Do-Thi & Thao Nguyen-Trang, 2023. "Profitability of Ichimoku-Based Trading Rule in Vietnam Stock Market in the Context of the COVID-19 Outbreak," Computational Economics, Springer;Society for Computational Economics, vol. 62(4), pages 1781-1799, December.

    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. 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.
    2. Michael D. McKenzie, 2007. "Technical Trading Rules in Emerging Markets and the 1997 Asian Currency Crises," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 43(4), pages 46-73, August.
    3. Yen-Sen Ni & Jen-Tsai Lee & Yi-Ching Liao, 2013. "Do variable length moving average trading rules matter during a financial crisis period?," Applied Economics Letters, Taylor & Francis Journals, vol. 20(2), pages 135-141, February.
    4. Alexandros Milionis & Evangelia Papanagiotou, 2009. "A study of the predictive performance of the moving average trading rule as applied to NYSE, the Athens Stock Exchange and the Vienna Stock Exchange: sensitivity analysis and implications for weak-for," Applied Financial Economics, Taylor & Francis Journals, vol. 19(14), pages 1171-1186.
    5. Metghalchi, Massoud & Chen, Chien-Ping & Hayes, Linda A., 2015. "History of share prices and market efficiency of the Madrid general stock index," International Review of Financial Analysis, Elsevier, vol. 40(C), pages 178-184.
    6. 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.
    7. Marshall, Ben R. & Cahan, Rochester H., 2005. "Is technical analysis profitable on a stock market which has characteristics that suggest it may be inefficient?," Research in International Business and Finance, Elsevier, vol. 19(3), pages 384-398, September.
    8. Massoud Metghalchi & Linda A. Hayes & Farhang Niroomand, 2019. "A technical approach to equity investing in emerging markets," Review of Financial Economics, John Wiley & Sons, vol. 37(3), pages 389-403, July.
    9. Ming-Ming, Lai & Siok-Hwa, Lau, 2006. "The profitability of the simple moving averages and trading range breakout in the Asian stock markets," Journal of Asian Economics, Elsevier, vol. 17(1), pages 144-170, February.
    10. Kung, James J., 2009. "Predictability of Technical Trading Rules: Evidence from the Taiwan Stock Market," Review of Applied Economics, Lincoln University, Department of Financial and Business Systems, vol. 5(1-2), pages 1-17, March.
    11. Salma Khand & Vivake Anand & Mohammad Nadeem Qureshi, 2020. "The Predictability and Profitability of Simple Moving Averages and Trading Range Breakout Rules in the Pakistan Stock Market," Review of Pacific Basin Financial Markets and Policies (RPBFMP), World Scientific Publishing Co. Pte. Ltd., vol. 23(01), pages 1-38, March.
    12. Wang, Zi-Mei & Chiao, Chaoshin & Chang, Ya-Ting, 2012. "Technical analyses and order submission behaviors: Evidence from an emerging market," International Review of Economics & Finance, Elsevier, vol. 24(C), pages 109-128.
    13. Michael McAleer & John Suen & Wing Keung Wong, 2016. "Profiteering from the Dot-Com Bubble, Subprime Crisis and Asian Financial Crisis," The Japanese Economic Review, Japanese Economic Association, vol. 67(3), pages 257-279, September.
    14. 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.
    15. Zhu, Hong & Jiang, Zhi-Qiang & Li, Sai-Ping & Zhou, Wei-Xing, 2015. "Profitability of simple technical trading rules of Chinese stock exchange indexes," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 439(C), pages 75-84.
    16. Elaine Y. L. Loh, 2007. "An alternative test for weak form efficiency based on technical analysis," Applied Financial Economics, Taylor & Francis Journals, vol. 17(12), pages 1003-1012.
    17. Farias Nazário, Rodolfo Toríbio & e Silva, Jéssica Lima & Sobreiro, Vinicius Amorim & Kimura, Herbert, 2017. "A literature review of technical analysis on stock markets," The Quarterly Review of Economics and Finance, Elsevier, vol. 66(C), pages 115-126.
    18. 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.
    19. Metghalchi, Massoud & Chang, Yung-Ho & Marcucci, Juri, 2008. "Is the Swedish stock market efficient? Evidence from some simple trading rules," International Review of Financial Analysis, Elsevier, vol. 17(3), pages 475-490, June.
    20. Hatgioannides, John & Mesomeris, Spyros, 2007. "On the returns generating process and the profitability of trading rules in emerging capital markets," Journal of International Money and Finance, Elsevier, vol. 26(6), pages 948-973, October.

    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:kap:apfinm:v:28:y:2021:i:4:d:10.1007_s10690-021-09337-5. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.