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The impact of data snooping on the testing of technical analysis: An empirical study of Asian stock markets

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  • Chen, Cheng-Wei
  • Huang, Chin-Sheng
  • Lai, Hung-Wei

Abstract

The primary aim of this study is to investigate the validity and predictability of technical analysis in eight Asian equity markets. We employ the bootstrap tests of White (2000) and Hansen (2005) to determine whether any superior trading rule is found to exist amongst the 'universe' of technical trading rules identified by Sullivan et al. (1999). We use these powerful bootstrap tests to ascertain the profitability of technical analysis, along with two institutional adjustments for non-synchronous trading and transaction costs. The empirical results indicate that these three elements, data snooping, non-synchronous trading and transaction costs, have significant impact on the overall performance of technical analysis; indeed, the results for these eight Asian stock markets support the efficient market hypothesis, demonstrating that the generation of economic profits through the use of technical analysis is extremely unlikely with these particular markets.

Suggested Citation

  • 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.
    • Handle: RePEc:eee:asieco:v:20:y:2009:i:5:p:580-591
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    1. West, Kenneth D, 1996. "Asymptotic Inference about Predictive Ability," Econometrica, Econometric Society, vol. 64(5), pages 1067-1084, September.
    2. Kenneth A. Kavajecz, 2004. "Technical Analysis and Liquidity Provision," Review of Financial Studies, Society for Financial Studies, vol. 17(4), pages 1043-1071.
    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. Grossman, Sanford J & Stiglitz, Joseph E, 1980. "On the Impossibility of Informationally Efficient Markets," American Economic Review, American Economic Association, vol. 70(3), pages 393-408, June.
    5. De Long, J Bradford & Andrei Shleifer & Lawrence H. Summers & Robert J. Waldmann, 1990. "Noise Trader Risk in Financial Markets," Journal of Political Economy, University of Chicago Press, vol. 98(4), pages 703-738, August.
    6. Treynor, Jack L & Ferguson, Robert, 1985. "In Defense of Technical Analysis," Journal of Finance, American Finance Association, vol. 40(3), pages 757-773, July.
    7. 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.
    8. 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.
    9. 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.
    10. 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.
    11. Taylor, Mark P. & Allen, Helen, 1992. "The use of technical analysis in the foreign exchange market," Journal of International Money and Finance, Elsevier, vol. 11(3), pages 304-314, June.
    12. 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.
    13. Halbert White, 2000. "A Reality Check for Data Snooping," Econometrica, Econometric Society, vol. 68(5), pages 1097-1126, September.
    14. 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.
    15. Mahendra Raj & David Thurston, 1996. "Effectiveness of simple technical trading rules in the Hong Kong futures markets," Applied Economics Letters, Taylor & Francis Journals, vol. 3(1), pages 33-36.
    16. Hudson, Robert & Dempsey, Michael & Keasey, Kevin, 1996. "A note on the weak form efficiency of capital markets: The application of simple technical trading rules to UK stock prices - 1935 to 1994," Journal of Banking & Finance, Elsevier, vol. 20(6), pages 1121-1132, July.
    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 1705-1770, August.
    18. Bonser-Neal, Catherine & Linnan, David & Neal, Robert, 1999. "Emerging market transaction costs: Evidence from Indonesia," Pacific-Basin Finance Journal, Elsevier, vol. 7(2), pages 103-127, May.
    19. Hansen, Peter Reinhard, 2005. "A Test for Superior Predictive Ability," Journal of Business & Economic Statistics, American Statistical Association, vol. 23, pages 365-380, October.
    20. Diebold, Francis X & Mariano, Roberto S, 2002. "Comparing Predictive Accuracy," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(1), pages 134-144, January.
    21. 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.
    22. Jensen, Michael C & Bennington, George A, 1970. "Random Walks and Technical Theories: Some Additional Evidence," Journal of Finance, American Finance Association, vol. 25(2), pages 469-482, May.
    23. J. Andrew Coutts & Kwong-C. Cheung, 2000. "Trading rules and stock returns: some preliminary short run evidence from the Hang Seng 1985-1997," Applied Financial Economics, Taylor & Francis Journals, vol. 10(6), pages 579-586.
    24. Fama, Eugene F. & French, Kenneth R., 1993. "Common risk factors in the returns on stocks and bonds," Journal of Financial Economics, Elsevier, vol. 33(1), pages 3-56, February.
    25. 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.
    26. Cheung, Yin-Wong & Chinn, Menzie David, 2001. "Currency traders and exchange rate dynamics: a survey of the US market," Journal of International Money and Finance, Elsevier, vol. 20(4), pages 439-471, August.
    27. Black, Fischer, 1986. "Noise," Journal of Finance, American Finance Association, vol. 41(3), pages 529-543, July.
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    2. José A. Roldán-Casas & Mª B. García-Moreno García, 2022. "A procedure for testing the hypothesis of weak efficiency in financial markets: a Monte Carlo simulation," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 31(5), pages 1289-1327, December.
    3. A. Olasolo & M. A. Pérez & V. Ruiz, 2016. "Active investment strategies in the Spanish futures market: a solution to avoid data snooping bias," Applied Economics Letters, Taylor & Francis Journals, vol. 23(9), pages 609-613, June.
    4. Kevin Rink, 2023. "The predictive ability of technical trading rules: an empirical analysis of developed and emerging equity markets," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 37(4), pages 403-456, December.
    5. Juan Benjamín Duarte Duarte & Juan Manuel Mascare?nas Pérez-Iñigo, 2014. "Comprobación de la eficiencia débil en los principales mercados financieros latinoamericanos," Estudios Gerenciales, Universidad Icesi, November.
    6. Luís Lobato Macedo & Pedro Godinho & Maria João Alves, 2020. "A Comparative Study of Technical Trading Strategies Using a Genetic Algorithm," Computational Economics, Springer;Society for Computational Economics, vol. 55(1), pages 349-381, January.
    7. Shan Wang & Zhi-Qiang Jiang & Sai-Ping Li & Wei-Xing Zhou, 2015. "Testing the performance of technical trading rules in the Chinese market," Papers 1504.06397, arXiv.org.
    8. Urquhart, Andrew & Gebka, Bartosz & Hudson, Robert, 2015. "How exactly do markets adapt? Evidence from the moving average rule in three developed markets," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 38(C), pages 127-147.
    9. 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).
    10. Panha Heng & Scott J. Niblock, 2014. "Trading with Tigers: A Technical Analysis of Southeast Asian Stock Index Futures," International Economic Journal, Taylor & Francis Journals, vol. 28(4), pages 679-692, December.
    11. Yuze Lu & Hailong Zhang & Qiwen Guo, 2023. "Stock and market index prediction using Informer network," Papers 2305.14382, arXiv.org.
    12. 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.

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