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Applying Technical Trading Rules to Beat Long-Term Investing: Evidence from Asian Markets

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  • Thomas S. Coe
  • Kittipong Laosethakul

    (Sacred Heart University)

Abstract

We provide evidence that the use of technical trading rules provides traders the opportunity to generate profits from actively buying and selling individual stocks across Asian markets. We test the trading performance of three widely used technical trading strategies, the Arithmetic Moving Average, the Relative Strength Index, and the Stochastic Oscillator, as well as variations to each trading strategy. We compare the results of these trading rules to a long-term buy-and-hold strategy across 4822 stocks traded in 39 Asian countries. Our results, when applying a simple behavior intervention filter of only selling a position when a trade is profitable, show that these technical trading rules, on average, were able to outperform the buy-and-hold strategy for 66% of the stocks listed in our sample. Additionally, given any of the listed Asian stocks, we found that, on average, a trader could apply any technical trading strategy and have a greater than 50–50 chance of outperforming the buy-and hold strategy for that stock for 63% of all stocks.

Suggested Citation

  • Thomas S. Coe & Kittipong Laosethakul, 2021. "Applying Technical Trading Rules to Beat Long-Term Investing: Evidence from Asian Markets," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 28(4), pages 587-611, December.
    • Handle: RePEc:kap:apfinm:v:28:y:2021:i:4:d:10.1007_s10690-021-09337-5
    DOI: 10.1007/s10690-021-09337-5
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    References listed on IDEAS

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    Cited by:

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    2. Day, Min-Yuh & Ni, Yensen, 2023. "Do clean energy indices outperform using contrarian strategies based on contrarian trading rules?," Energy, Elsevier, vol. 272(C).
    3. Ha Che-Ngoc & Nga Do-Thi & Thao Nguyen-Trang, 2023. "Profitability of Ichimoku-Based Trading Rule in Vietnam Stock Market in the Context of the COVID-19 Outbreak," Computational Economics, Springer;Society for Computational Economics, vol. 62(4), pages 1781-1799, December.
    4. Day, Min-Yuh & Ni, Yensen, 2023. "The profitability of seasonal trading timing: Insights from energy-related markets," Energy Economics, Elsevier, vol. 128(C).
    5. Cristiana Tudor & Robert Sova, 2025. "An automated adaptive trading system for enhanced performance of emerging market portfolios," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 11(1), pages 1-39, December.

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