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MA trading rules, herding behaviors, and stock market overreaction

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  • Ni, Yensen
  • Liao, Yi-Ching
  • Huang, Paoyu

Abstract

We determine whether investors profit from employing moving average trading rules that consider either “wide” or “in-depth” concerns. Our remarkable findings are as follows: First, investors benefit from purchasing the constituent stocks of SSE50 as dead crosses emerge. These stocks may be the result of the herding behaviors of individual investors who account for over 80% of investors in China's stock markets. Second, negative weekly returns increase in trading the constituent stocks of DJ30 and FTSE100 because returns increase considerably on golden-cross days as a result of stock price overreaction. These results remain robust by concerning investors' risk aversion, and even high risk aversion as investors suffer losses. In addition, our findings imply that stock market overreaction and herding behaviors are incorporated into technical analysis.

Suggested Citation

  • 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.
  • Handle: RePEc:eee:reveco:v:39:y:2015:i:c:p:253-265
    DOI: 10.1016/j.iref.2015.04.009
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    Cited by:

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    4. Jaber Yasmina, 2020. "Transactions Volume, Exchange Direction and Asymmetry of Volatility in Emerging Market: Evidence From Tunisian Stock Exchange," International Journal of Financial Research, International Journal of Financial Research, Sciedu Press, vol. 11(6), pages 318-336, December.
    5. Yensen Ni & Min-Yuh Day & Paoyu Huang, 2020. "Trading stocks following sharp movements in the USDX, GBP/USD, and USD/CNY," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 6(1), pages 1-17, December.
    6. Wu, Manhwa & Huang, Paoyu & Ni, Yensen, 2017. "Capital liberalization and various financial markets: Evidence from Taiwan," The Quarterly Review of Economics and Finance, Elsevier, vol. 66(C), pages 265-274.
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    9. Jying‐Nan Wang & Hung‐Chun Liu & Jiangze Du & Yuan‐Teng Hsu, 2019. "Economic benefits of technical analysis in portfolio management: Evidence from global stock markets," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 24(2), pages 890-902, April.
    10. Manhwa Wu & Paoyu Huang & Yensen Ni, 2017. "Investing strategies as continuous rising (falling) share prices released," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 41(4), pages 763-773, October.
    11. Camillo Lento & Nikola Gradojevic, 2022. "The Profitability of Technical Analysis during the COVID-19 Market Meltdown," JRFM, MDPI, vol. 15(5), pages 1-19, April.
    12. Chia-Lin Chang & Jukka Ilomäki & Hannu Laurila & Michael McAleer, 2018. "Market Timing with Moving Averages for Fossil Fuel and Renewable Energy Stocks," Documentos de Trabajo del ICAE 2018-24, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico.
    13. Chia-Lin Chang & Jukka Ilomäki & Hannu Laurila & Michael McAleer, 2018. "Moving Average Market Timing in European Energy Markets: Production Versus Emissions," Energies, MDPI, vol. 11(12), pages 1-24, November.
    14. 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.
    15. Chien-Liang Chiu & Paoyu Huang & Min-Yuh Day & Yensen Ni & Yuhsin Chen, 2024. "Mastery of “Monthly Effects”: Big Data Insights into Contrarian Strategies for DJI 30 and NDX 100 Stocks over a Two-Decade Period," Mathematics, MDPI, vol. 12(2), pages 1-22, January.
    16. 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.
    17. Ni, Yensen & Wu, Manhwa & Day, Min-Yuh & Huang, Paoyu, 2020. "Do sharp movements in oil prices matter for stock markets?," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 539(C).
    18. Ni, Yensen & Day, Min-Yuh & Huang, Paoyu & Yu, Shang-Ru, 2020. "The profitability of Bollinger Bands: Evidence from the constituent stocks of Taiwan 50," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 551(C).
    19. Yensen Ni & Yirung Cheng & Yulu Liao & Paoyu Huang, 2022. "Does board structure affect stock price overshooting informativeness measured by stochastic oscillator indicators?," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(2), pages 2290-2302, April.
    20. Ni, Yensen & Cheng, Yirung & Huang, Paoyu & Day, Min-Yuh, 2018. "Trading strategies in terms of continuous rising (falling) prices or continuous bullish (bearish) candlesticks emitted," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 501(C), pages 188-204.

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    More about this item

    Keywords

    Moving average; Herding behavior; Overreaction;
    All these keywords.

    JEL classification:

    • G02 - Financial Economics - - General - - - Behavioral Finance: Underlying Principles
    • 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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