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Intertemporal profitability and the stability of technical analysis: evidences from the Hong Kong stock exchange

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  • William Cheung
  • Keith Lam
  • HangFai Yeung

Abstract

This study investigates the impact of market integration on the profitability of two simple and popular technical trading rules, the Simple Moving Average (SMA) and the Trading Range Break (TRB) in Hong Kong. Using data from 1972 to 2006, we find that the SMA (1, 50) consistently outperforms the market before the integration of stock exchanges in 1986. Under the (1, 50) rule, a variable length moving average performs better than the fixed length moving average rule by 2.5 to 5% (annual) before transaction costs because it includes the information of the first 9 days into investors' decision. The results are robust to the out of sample tests for the validity of the profitability of the trading rules. The returns of the trading range break rules are insignificant over the 35-year span. Our results support the conjecture that stock market integration may lead to better information efficiency. The findings of significant pre-1986 profits and insignificant post-1986 profits, contradict previous findings that returns are predictable in Hong Kong, suggesting that the Hong Kong stock market may be weak-form efficient after 1986. Overall, our results suggest that technical analysis matters for asset pricing.

Suggested Citation

  • William Cheung & Keith Lam & HangFai Yeung, 2011. "Intertemporal profitability and the stability of technical analysis: evidences from the Hong Kong stock exchange," Applied Economics, Taylor & Francis Journals, vol. 43(15), pages 1945-1963.
    • Handle: RePEc:taf:applec:v:43:y:2011:i:15:p:1945-1963
    DOI: 10.1080/00036840902817805
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    References listed on IDEAS

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    1. Isakov, D. & Hollistein, M., 1998. "Application of Simple Technical Trading Rules to Swiss Stock Prices: Is It Profitable?," Papers 98.2, Ecole des Hautes Etudes Commerciales, Universite de Geneve-.
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    Cited by:

    1. Wang, Lijun & An, Haizhong & Liu, Xiaojia & Huang, Xuan, 2016. "Selecting dynamic moving average trading rules in the crude oil futures market using a genetic approach," Applied Energy, Elsevier, vol. 162(C), pages 1608-1618.
    2. Tsai, Yi-Cheng & Lei, Chin-Laung & Cheung, William & Wu, Chung-Shu & Ho, Jan-Ming & Wang, Chuan-Ju, 2018. "Exploring the Persistent Behavior of Financial Markets," Finance Research Letters, Elsevier, vol. 24(C), pages 199-220.
    3. Eero P䴤ri & Mika Vilska, 2014. "Performance of moving average trading strategies over varying stock market conditions: the Finnish evidence," Applied Economics, Taylor & Francis Journals, vol. 46(24), pages 2851-2872, August.
    4. Lijun Wang & Haizhong An & Xiaohua Xia & Xiaojia Liu & Xiaoqi Sun & Xuan Huang, 2014. "Generating Moving Average Trading Rules on the Oil Futures Market with Genetic Algorithms," Mathematical Problems in Engineering, Hindawi, vol. 2014, pages 1-10, May.

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