IDEAS home Printed from https://ideas.repec.org/a/eee/ecofin/v51y2020ics1062940818302250.html
   My bibliography  Save this article

Testing the performance of technical analysis and sentiment-TAR trading rules in the Malaysian stock market

Author

Listed:
  • Tan, Siow-Hooi
  • Lai, Ming-Ming
  • Tey, Eng-Xin
  • Chong, Lee-Lee

Abstract

This study carries out investigation of technical analysis and Sentiment-Threshold Autoregressive (Sentiment-TAR) trading rules in the Malaysian stock market, using daily data from Jan 1, 2001 through December 31, 2016. The findings reveal that while the Sentiment-TAR trading rules (more specifically SentimentWORLD-TAR) have better predictive power than technical trading rule, the magnitude of predictability is shown to vary with sectors. Robustness of results is further verified by in- and out-of-sample test and bootstrap analysis. As expected, the inclusion of transaction costs eliminates the trading profits for the majority of the trading rules. Nevertheless, results reveal that investors can gain substantially by combining Sentiment-TAR and TRB rules and by investing in certain sectors.

Suggested Citation

  • Tan, Siow-Hooi & Lai, Ming-Ming & Tey, Eng-Xin & Chong, Lee-Lee, 2020. "Testing the performance of technical analysis and sentiment-TAR trading rules in the Malaysian stock market," The North American Journal of Economics and Finance, Elsevier, vol. 51(C).
    • Handle: RePEc:eee:ecofin:v:51:y:2020:i:c:s1062940818302250
    DOI: 10.1016/j.najef.2018.12.007
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1062940818302250
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.najef.2018.12.007?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. Hong, Harrison & Torous, Walter & Valkanov, Rossen, 2007. "Do industries lead stock markets?," Journal of Financial Economics, Elsevier, vol. 83(2), pages 367-396, February.
    2. Westerlund, Joakim & Narayan, Paresh Kumar & Zheng, Xinwei, 2015. "Testing for stock return predictability in a large Chinese panel," Emerging Markets Review, Elsevier, vol. 24(C), pages 81-100.
    3. 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.
    4. Baker, Malcolm & Stein, Jeremy C., 2004. "Market liquidity as a sentiment indicator," Journal of Financial Markets, Elsevier, vol. 7(3), pages 271-299, June.
    5. Jasman Tuyon & Zamri Ahmad & Hylmee Matahir, 2016. "The Roles of Investor Sentiment in Malaysian Stock Market," Asian Academy of Management Journal of Accounting and Finance (AAMJAF), Penerbit Universiti Sains Malaysia, vol. 12(Suppl. 1), pages 43-75.
    6. Malcolm Baker & Jeffrey Wurgler, 2006. "Investor Sentiment and the Cross‐Section of Stock Returns," Journal of Finance, American Finance Association, vol. 61(4), pages 1645-1680, August.
    7. Joakim Westerlund & Paresh Narayan, 2015. "A Random Coefficient Approach to the Predictability of Stock Returns in Panels," Journal of Financial Econometrics, Oxford University Press, vol. 13(3), pages 605-664.
    8. Jongwanich, Juthathip & Gochoco-Bautista, Maria Socorro & Lee, Jong-Wha, 2011. "When are Capital Controls Effective? Evidence from Malaysia and Thailand," ADB Economics Working Paper Series 251, Asian Development Bank.
    9. 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.
    10. Neely, Christopher J. & Weller, Paul A., 2001. "Technical analysis and central bank intervention," Journal of International Money and Finance, Elsevier, vol. 20(7), pages 949-970, December.
    11. Bannigidadmath, Deepa & Narayan, Paresh Kumar, 2016. "Stock return predictability and determinants of predictability and profits," Emerging Markets Review, Elsevier, vol. 26(C), pages 153-173.
    12. Malcolm Baker & Jeffrey Wurgler, 2007. "Investor Sentiment in the Stock Market," Journal of Economic Perspectives, American Economic Association, vol. 21(2), pages 129-152, Spring.
    13. Bruce E. Hansen, 2000. "Sample Splitting and Threshold Estimation," Econometrica, Econometric Society, vol. 68(3), pages 575-604, May.
    14. Narayan, Paresh Kumar & Ahmed, Huson Ali & Sharma, Susan Sunila & K.P., Prabheesh, 2014. "How profitable is the Indian stock market?," Pacific-Basin Finance Journal, Elsevier, vol. 30(C), pages 44-61.
    15. Juthathip Jongwanich & Maria Socorro Gochoco-Bautista & Jong-Wha Lee, 2011. "When are Capital Controls Effective? Evidence from Malaysia and Thailand," International Economic Journal, Taylor & Francis Journals, vol. 25(4), pages 619-651, December.
    16. Christopher J. Neely & David E. Rapach & Jun Tu & Guofu Zhou, 2014. "Forecasting the Equity Risk Premium: The Role of Technical Indicators," Management Science, INFORMS, vol. 60(7), pages 1772-1791, July.
    17. Yang, Chunpeng & Zhou, Liyun, 2015. "Investor trading behavior, investor sentiment and asset prices," The North American Journal of Economics and Finance, Elsevier, vol. 34(C), pages 42-62.
    18. Sharma, Susan Sunila & Narayan, Paresh Kumar, 2014. "New evidence on turn-of-the-month effects," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 29(C), pages 92-108.
    19. Gunasekarage, Abeyratna & Power, David M., 2001. "The profitability of moving average trading rules in South Asian stock markets," Emerging Markets Review, Elsevier, vol. 2(1), pages 17-33, March.
    20. Narayan, Paresh Kumar & Sharma, Susan Sunila, 2011. "New evidence on oil price and firm returns," Journal of Banking & Finance, Elsevier, vol. 35(12), pages 3253-3262.
    21. Kadilli, Anjeza, 2015. "Predictability of stock returns of financial companies and the role of investor sentiment: A multi-country analysis," Journal of Financial Stability, Elsevier, vol. 21(C), pages 26-45.
    22. Perez-Rodriguez, Jorge V. & Torra, Salvador & Andrada-Felix, Julian, 2005. "STAR and ANN models: forecasting performance on the Spanish "Ibex-35" stock index," Journal of Empirical Finance, Elsevier, vol. 12(3), pages 490-509, June.
    23. Haiqiang Chen & Terence Tai-Leung Chong & Xin Duan, 2010. "A principal-component approach to measuring investor sentiment," Quantitative Finance, Taylor & Francis Journals, vol. 10(4), pages 339-347.
    24. Khan, Mohammad Tariqul Islam & Tan, Siow-Hooi & Chong, Lee-Lee, 2017. "How past perceived portfolio returns affect financial behaviors—The underlying psychological mechanism," Research in International Business and Finance, Elsevier, vol. 42(C), pages 1478-1488.
    25. Terence Tai-Leung Chong & Tau-Hing Lam, 2010. "Predictability of nonlinear trading rules in the U.S. stock market," Quantitative Finance, Taylor & Francis Journals, vol. 10(9), pages 1067-1076.
    26. Narayan, Paresh Kumar & Bannigidadmath, Deepa, 2015. "Are Indian stock returns predictable?," Journal of Banking & Finance, Elsevier, vol. 58(C), pages 506-531.
    27. 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.
    28. 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.
    29. Narayan, Paresh Kumar, 2018. "Profitability of technology-investing Islamic and non-Islamic stock markets," Pacific-Basin Finance Journal, Elsevier, vol. 52(C), pages 70-81.
    30. Deepa & Paresh K Narayan, "undated". "Are Indian Stock Returns Predictable?," Working Papers 2015_07, Deakin University, Department of Economics.
    31. 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.
    32. Halbert White, 2000. "A Reality Check for Data Snooping," Econometrica, Econometric Society, vol. 68(5), pages 1097-1126, September.
    33. 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.
    34. Chou, Pin-Huang & Ho, Po-Hsin & Ko, Kuan-Cheng, 2012. "Do industries matter in explaining stock returns and asset-pricing anomalies?," Journal of Banking & Finance, Elsevier, vol. 36(2), pages 355-370.
    35. 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.
    36. Hansen, Peter Reinhard, 2005. "A Test for Superior Predictive Ability," Journal of Business & Economic Statistics, American Statistical Association, vol. 23, pages 365-380, October.
    37. Narayan, Paresh Kumar & Ahmed, Huson Ali & Narayan, Seema, 2017. "Can investors gain from investing in certain sectors?," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 48(C), pages 160-177.
    38. 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.
    39. Schmeling, Maik, 2009. "Investor sentiment and stock returns: Some international evidence," Journal of Empirical Finance, Elsevier, vol. 16(3), pages 394-408, June.
    40. Narayan, Paresh Kumar & Narayan, Seema & Westerlund, Joakim, 2015. "Do order imbalances predict Chinese stock returns? New evidence from intraday data," Pacific-Basin Finance Journal, Elsevier, vol. 34(C), pages 136-151.
    41. Karpoff, Jonathan M., 1987. "The Relation between Price Changes and Trading Volume: A Survey," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 22(1), pages 109-126, March.
    42. Lo, Andrew W & MacKinlay, A Craig, 1990. "Data-Snooping Biases in Tests of Financial Asset Pricing Models," Review of Financial Studies, Society for Financial Studies, vol. 3(3), pages 431-467.
    43. Phan, Dinh Hoang Bach & Sharma, Susan Sunila & Tran, Vuong Thao, 2018. "Can economic policy uncertainty predict stock returns? Global evidence," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 55(C), pages 134-150.
    44. Joakim Westerlund & Paresh K Narayan & Xinwei Zheng, "undated". "Testing For Stock Return Predictability In A Large Chinese Panel," Working Papers 2015_11, Deakin University, Department of Economics.
    45. Terence Tai-Leung Chong & Tau-Hing Lam, 2013. "How To Make A Profitable Trading Strategy More Profitable?," The Singapore Economic Review (SER), World Scientific Publishing Co. Pte. Ltd., vol. 58(03), pages 1-17.
    46. Buchanan, Bonnie G. & English II, Philip C. & Gordon, Rachel, 2011. "Emerging market benefits, investability and the rule of law," Emerging Markets Review, Elsevier, vol. 12(1), pages 47-60, March.
    47. Adrian R. Pagan & Kirill A. Sossounov, 2003. "A simple framework for analysing bull and bear markets," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 18(1), pages 23-46.
    48. Menkhoff, Lukas, 2010. "The use of technical analysis by fund managers: International evidence," Journal of Banking & Finance, Elsevier, vol. 34(11), pages 2573-2586, November.
    49. 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.
    50. Chen, Cheng-Wei & Huang, Chin-Sheng & Lai, Hung-Wei, 2009. "The impact of data snooping on the testing of technical analysis: An empirical study of Asian stock markets," Journal of Asian Economics, Elsevier, vol. 20(5), pages 580-591, September.
    51. 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)

    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. 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.
    2. Day, Min-Yuh & Ni, Yensen & Huang, Paoyu, 2019. "Trading as sharp movements in oil prices and technical trading signals emitted with big data concerns," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 525(C), pages 349-372.
    3. Bannigidadmath, Deepa & Narayan, Paresh Kumar, 2016. "Stock return predictability and determinants of predictability and profits," Emerging Markets Review, Elsevier, vol. 26(C), pages 153-173.
    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. Wen-Jun Xue & Li-Wen Zhang, 2016. "Stock Return Autocorrelations and Predictability in the Chinese Stock Market: Evidence from Threshold Quantile Autoregressive Models," Working Papers 1605, Florida International University, Department of Economics.
    6. Phan, Dinh Hoang Bach & Sharma, Susan Sunila & Tran, Vuong Thao, 2018. "Can economic policy uncertainty predict stock returns? Global evidence," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 55(C), pages 134-150.
    7. Xue, Wen-Jun & Zhang, Li-Wen, 2017. "Stock return autocorrelations and predictability in the Chinese stock market—Evidence from threshold quantile autoregressive models," Economic Modelling, Elsevier, vol. 60(C), pages 391-401.
    8. Hung, Chiayu & Lai, Hung-Neng, 2022. "Information asymmetry and the profitability of technical analysis," Journal of Banking & Finance, Elsevier, vol. 134(C).
    9. Christopher J. Neely & David E. Rapach & Jun Tu & Guofu Zhou, 2014. "Forecasting the Equity Risk Premium: The Role of Technical Indicators," Management Science, INFORMS, vol. 60(7), pages 1772-1791, July.
    10. Fong, Tom Pak Wing & Wu, Shui Tang, 2020. "Predictability in sovereign bond returns using technical trading rules: Do developed and emerging markets differ?," The North American Journal of Economics and Finance, Elsevier, vol. 51(C).
    11. Christopher J. Neely & Paul A. Weller, 2011. "Technical analysis in the foreign exchange market," Working Papers 2011-001, Federal Reserve Bank of St. Louis.
    12. 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.
    13. Haiqiang Chen & Terence Tai Leung Chong & Yingni She, 2014. "A principal component approach to measuring investor sentiment in China," Quantitative Finance, Taylor & Francis Journals, vol. 14(4), pages 573-579, April.
    14. 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.
    15. 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.
    16. Chen, Cheng-Wei & Huang, Chin-Sheng & Lai, Hung-Wei, 2009. "The impact of data snooping on the testing of technical analysis: An empirical study of Asian stock markets," Journal of Asian Economics, Elsevier, vol. 20(5), pages 580-591, September.
    17. 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.
    18. Devpura, Neluka & Narayan, Paresh Kumar & Sharma, Susan Sunila, 2018. "Is stock return predictability time-varying?," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 52(C), pages 152-172.
    19. Flavio Ivo Riedlinger & João Nicolau, 2020. "The Profitability in the FTSE 100 Index: A New Markov Chain Approach," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 27(1), pages 61-81, March.
    20. Rapach, David & Zhou, Guofu, 2013. "Forecasting Stock Returns," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 328-383, Elsevier.

    More about this item

    Keywords

    Sentiment-TAR; Technical trading rules; Malaysia; Data snooping; Transaction costs;
    All these keywords.

    JEL classification:

    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets

    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:ecofin:v:51:y:2020:i:c:s1062940818302250. 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/inca/620163 .

    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.