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The real-life performance of market timing with moving average and time-series momentum rules

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  • Valeriy Zakamulin

    (School of Business and Law, University of Agder)

Abstract

In this article, we revisit the myths regarding the superior performance of market timing strategies based on moving average and time-series momentum rules. These active timing strategies are very appealing to investors because of their extraordinary simplicity and because they promise substantial advantages over their passive counterparts. However, the ‘too good to be true’ reported performance of these market timing rules raises a legitimate concern as to whether this performance is realistic and whether investors can expect that future performance will be the same as the documented historical performance. We argue that the reported performance of market timing strategies usually contains a considerable data-mining bias and ignores important market frictions. To address these issues, we perform out-of-sample tests of these two timing models in which we account for realistic transaction costs. Our findings reveal that the performance of market timing strategies is highly overstated, to say the least.

Suggested Citation

  • Valeriy Zakamulin, 2014. "The real-life performance of market timing with moving average and time-series momentum rules," Journal of Asset Management, Palgrave Macmillan, vol. 15(4), pages 261-278, August.
  • Handle: RePEc:pal:assmgt:v:15:y:2014:i:4:d:10.1057_jam.2014.25
    DOI: 10.1057/jam.2014.25
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    Cited by:

    1. Inoua, Sabiou M. & Smith, Vernon L., 2023. "A classical model of speculative asset price dynamics," Journal of Behavioral and Experimental Finance, Elsevier, vol. 37(C).
    2. Zakamulin, Valeriy & Giner, Javier, 2022. "Time series momentum in the US stock market: Empirical evidence and theoretical analysis," International Review of Financial Analysis, Elsevier, vol. 82(C).
    3. Valeriy Zakamulin & Javier Giner, 2020. "Trend following with momentum versus moving averages: a tale of differences," Quantitative Finance, Taylor & Francis Journals, vol. 20(6), pages 985-1007, June.
    4. Hubert Dichtl, 2020. "Investing in the S&P 500 index: Can anything beat the buy‐and‐hold strategy?," Review of Financial Economics, John Wiley & Sons, vol. 38(2), pages 352-378, April.
    5. Strobel, Marcus & Auer, Benjamin R., 2018. "Does the predictive power of variable moving average rules vanish over time and can we explain such tendencies?," International Review of Economics & Finance, Elsevier, vol. 53(C), pages 168-184.
    6. Kuntz, Laura-Chloé, 2020. "Beta dispersion and market timing," Journal of Empirical Finance, Elsevier, vol. 59(C), pages 235-256.
    7. Afiruddin Tapa* & Mohd Hasimi Yaacob & Ahmad Husni Hamzah & Yean Soh Chuen, 2018. "Trading Performance Analysis: A Comparisons Between the Original MA Crossover and Modified MA Crossover Strategy," The Journal of Social Sciences Research, Academic Research Publishing Group, pages 933-941:6.
    8. Yafeng Qin & Guoyao Pan & Min Bai, 2020. "Improving market timing of time series momentum in the Chinese stock market," Applied Economics, Taylor & Francis Journals, vol. 52(43), pages 4711-4725, September.
    9. Shangkun Deng & Haoran Yu & Chenyang Wei & Tianxiang Yang & Shimada Tatsuro, 2021. "The profitability of Ichimoku Kinkohyo based trading rules in stock markets and FX markets," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(4), pages 5321-5336, October.
    10. Kuntz, Laura-Chloé, 2020. "Beta dispersion and market timing," Discussion Papers 46/2020, Deutsche Bundesbank.

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