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The rise and fall of technical trading rule success

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  • Taylor, Nick

Abstract

The purpose of this paper is to examine the performance of an important set of momentum-based technical trading rules (TTRs) applied to all members of the Dow Jones Industrial Average (DJIA) stock index over the period 1928–2012. Using a set of econometric models that permit time-variation in risk-adjusted returns to TTR portfolios, the results reveal that profits evolve slowly over time, are confined to particular episodes primarily from the mid-1960s to mid-1980s, and rely on the ability of investors to short-sell stocks. These findings are demonstrated to be consistent with theoretical models that predict a relationship between TTR performance and market conditions.

Suggested Citation

  • Taylor, Nick, 2014. "The rise and fall of technical trading rule success," Journal of Banking & Finance, Elsevier, vol. 40(C), pages 286-302.
  • Handle: RePEc:eee:jbfina:v:40:y:2014:i:c:p:286-302
    DOI: 10.1016/j.jbankfin.2013.12.004
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    8. H. -L. Shi & W. -X. Zhou, 2017. "Wax and wane of the cross-sectional momentum and contrarian effects: Evidence from the Chinese stock markets," Papers 1707.05552, arXiv.org.
    9. 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.
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    12. Chen, Chien-Hua & Su, Xuan-Qi & Lin, Jun-Biao, 2016. "The role of information uncertainty in moving-average technical analysis: A study of individual stock-option issuance in Taiwan," Finance Research Letters, Elsevier, vol. 18(C), pages 263-272.
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    15. 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.

    More about this item

    Keywords

    Technical trading rules; Short-selling; Market conditions;

    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading

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