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An analysis of trading strategies in eleven European stock markets

Author

Listed:
  • Suzanne Fifield
  • David Power
  • C. Donald Sinclair

Abstract

In recent years, the validity of the weak form efficient market hypothesis (EMH) has been called into question as several studies have uncovered evidence that technical trading rules have predictive ability with respect to both developed and emerging stock market indices. This study analyses the forecasting power of 2 of the most popular trading rules using index data for a selection of 11 European stock markets over the January 1991 to December 2000 period. The findings indicate that the emerging markets included in this paper are informationally inefficient; these markets displayed some degree of predictability in their share returns, although the developed markets did not. Furthermore, the results point to large differences in the performance of the rules examined; while small size filters consistently outperformed the buy-and-hold strategy in the emerging markets examined even after the consideration of transaction costs, the performance of the moving average rules was erratic and varied dramatically from market to market.

Suggested Citation

  • Suzanne Fifield & David Power & C. Donald Sinclair, 2005. "An analysis of trading strategies in eleven European stock markets," The European Journal of Finance, Taylor & Francis Journals, vol. 11(6), pages 531-548.
  • Handle: RePEc:taf:eurjfi:v:11:y:2005:i:6:p:531-548 DOI: 10.1080/1351847042000304099
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    References listed on IDEAS

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    1. Hendrik Bessembinder & Kalok Chan, 1998. "Market Efficiency and the Returns to Technical Analysis," Financial Management, Financial Management Association, vol. 27(2), Summer.
    2. Bessembinder, Hendrik & Chan, Kalok, 1995. "The profitability of technical trading rules in the Asian stock markets," Pacific-Basin Finance Journal, Elsevier, pages 257-284.
    3. 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.
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    Citations

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    Cited by:

    1. 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.
    2. David McMillan & Pako Thupayagale, 2011. "Measuring volatility persistence and long memory in the presence of structural breaks: Evidence from African stock markets," Managerial Finance, Emerald Group Publishing, vol. 37(3), pages 219-241, February.
    3. 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.
    4. Scholz, Peter & Walther, Ursula, 2011. "The trend is not your friend! Why empirical timing success is determined by the underlying's price characteristics and market efficiency is irrelevant," CPQF Working Paper Series 29, Frankfurt School of Finance and Management, Centre for Practical Quantitative Finance (CPQF).
    5. Ni, Yensen & Liao, Yi-Ching & Huang, Paoyu, 2015. "MA trading rules, herding behaviors, and stock market overreaction," International Review of Economics & Finance, Elsevier, vol. 39(C), pages 253-265.
    6. Huang, Paoyu & Ni, Yensen, 2017. "Board structure and stock price informativeness in terms of moving average rules," The Quarterly Review of Economics and Finance, Elsevier, vol. 63(C), pages 161-169.
    7. repec:eee:reveco:v:53:y:2018:i:c:p:168-184 is not listed on IDEAS
    8. Sensoy, Ahmet & Tabak, Benjamin M., 2015. "Time-varying long term memory in the European Union stock markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 436(C), pages 147-158.
    9. Collins G. Ntim & Kwaku K. Opong & Jo Danbolt & Frank Senyo Dewotor, 2011. "Testing the weak-form efficiency in African stock markets," Managerial Finance, Emerald Group Publishing, vol. 37(3), pages 195-218, February.
    10. A. Sensoy & Benjamin Miranda Tabak, 2013. "How much random does European Union walk? A time-varying long memory analysis," Working Papers Series 342, Central Bank of Brazil, Research Department.
    11. Scholz, Peter, 2012. "Size matters! How position sizing determines risk and return of technical timing strategies," CPQF Working Paper Series 31, Frankfurt School of Finance and Management, Centre for Practical Quantitative Finance (CPQF).

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