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An improved moving average technical trading rule

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  • Papailias, Fotis
  • Thomakos, Dimitrios D.

Abstract

This paper proposes a modified version of the widely used price and moving average cross-over trading strategies. The suggested approach (presented in its ‘long only’ version) is a combination of cross-over ‘buy’ signals and a dynamic threshold value which acts as a dynamic trailing stop. The trading behaviour and performance from this modified strategy are different from the standard approach with results showing that, on average, the proposed modification increases the cumulative return and the Sharpe ratio of the investor while exhibiting smaller maximum drawdown and smaller drawdown duration than the standard strategy.

Suggested Citation

  • Papailias, Fotis & Thomakos, Dimitrios D., 2015. "An improved moving average technical trading rule," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 428(C), pages 458-469.
    • Handle: RePEc:eee:phsmap:v:428:y:2015:i:c:p:458-469
    DOI: 10.1016/j.physa.2015.01.088
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    References listed on IDEAS

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    Cited by:

    1. Fernando F. Ferreira & A. Christian Silva & Ju-Yi Yen, 2019. "Detailed study of a moving average trading rule," Papers 1907.00212, arXiv.org.
    2. Hyungjun Park & Min Kyu Sim & Dong Gu Choi, 2019. "An intelligent financial portfolio trading strategy using deep Q-learning," Papers 1907.03665, arXiv.org, revised Nov 2019.
    3. Rob Hayward, 2018. "Foreign Exchange Speculation: An Event Study," IJFS, MDPI, vol. 6(1), pages 1-13, February.
    4. Konstandinos Chourmouziadis & Dimitra K. Chourmouziadou & Prodromos D. Chatzoglou, 2021. "Embedding Four Medium-Term Technical Indicators to an Intelligent Stock Trading Fuzzy System for Predicting: A Portfolio Management Approach," Computational Economics, Springer;Society for Computational Economics, vol. 57(4), pages 1183-1216, April.
    5. Li, Long & Bao, Si & Chen, Jing-Chao & Jiang, Tao, 2019. "A method to get a more stationary process and its application in finance with high-frequency data of Chinese index futures," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 525(C), pages 1405-1417.
    6. Chen, Shi & Bao, Si & Zhou, Yu, 2016. "The predictive power of Japanese candlestick charting in Chinese stock market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 457(C), pages 148-165.

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