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Investing Strategies for Trading Stocks as Overreaction Triggered by Technical Trading Rules with Big Data Concerns

Author

Listed:
  • Min-Yuh Day

    (Graduate Institute of Information Management, National Taipei University, New Taipei 23741, Taiwan)

  • Paoyu Huang

    (Department of International Business, Soochow University, Taipei 100006, Taiwan)

  • Yirung Cheng

    (Department of Management Sciences, Tamkang University, New Taipei 251301, Taiwan)

  • Yensen Ni

    (Department of Management Sciences, Tamkang University, New Taipei 251301, Taiwan)

Abstract
The meaning of technical indicators is to transmit overshooting signals, which lead investors to believe that they may beat the market when the overshooting signals have been triggered. The study aims to examine whether investors could exploit profits when the overreaction signals were revealed by some technical indicators. Meanwhile, several findings are exposed. First, momentum (contrarian) strategies are suggested as overbought (oversold) signals emitted, which differ from our cognition. Second, higher cumulative abnormal returns (CARs) are demonstrated for buying instead of selling the constituent stocks of SSE 50 when overshooting signs occurred, after comparing with those of DJIA 30 and FTSE 100. Third, since superior performance is revealed, investors may apply the BB trading rule instead of others as overreaction trading signals are emitted.

Suggested Citation

  • Min-Yuh Day & Paoyu Huang & Yirung Cheng & Yensen Ni, 2023. "Investing Strategies for Trading Stocks as Overreaction Triggered by Technical Trading Rules with Big Data Concerns," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(3), pages 148-161, October.
    • Handle: RePEc:rjr:romjef:v::y:2023:i:3:p:148-161
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    References listed on IDEAS

    as
    1. Suduan Chen, 2017. "Seasoned Equity Offerings or Capital Deductions? The Reaction of Stock Prices: Evidence from Taiwan," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 53(3), pages 644-660, March.
    2. Francesco Guidi & Rakesh Gupta & Suneel Maheshwari, 2011. "Weak-form Market Efficiency and Calendar Anomalies for Eastern Europe Equity Markets," Journal of Emerging Market Finance, Institute for Financial Management and Research, vol. 10(3), pages 337-389, December.
    3. Basak, Suryoday & Kar, Saibal & Saha, Snehanshu & Khaidem, Luckyson & Dey, Sudeepa Roy, 2019. "Predicting the direction of stock market prices using tree-based classifiers," The North American Journal of Economics and Finance, Elsevier, vol. 47(C), pages 552-567.
    4. 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.
    Full references (including those not matched with items on IDEAS)

    Citations

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    Cited by:

    1. 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.

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    More about this item

    Keywords

    Herding Behavior; Investing Strategies; Overreaction; Technical Indicators; Big Data;
    All these keywords.

    JEL classification:

    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions

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