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The profitability of regression-based trading rules for the Shanghai stock market
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The profitability of regression-based trading rules for the Shanghai stock market

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  • Groenewold, Nicolaas
  • Kan Tang, Sam Hak
  • Wu, Yanrui

Abstract

This paper uses daily Shanghai A share data to evaluate the profitability of trading rules based on the predictability found in the return series. We find that the value of the trading-rule-based portfolio at the end of our sample is between 2 and 11 times that of an equity-buy-and-hold portfolio. We assess the robustness of the results in various ways: by carrying out various statistical tests, by varying the period over which the evaluation is carried out, by using a recursive estimation procedure for the forecasting equation, by incorporating transactions costs, and by considering weekly and monthly data.

Suggested Citation

  • Groenewold, Nicolaas & Kan Tang, Sam Hak & Wu, Yanrui, 2008. "The profitability of regression-based trading rules for the Shanghai stock market," International Review of Financial Analysis, Elsevier, vol. 17(2), pages 411-430.
    • Handle: RePEc:eee:finana:v:17:y:2008:i:2:p:411-430
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    1. Hudson, Robert & Dempsey, Michael & Keasey, Kevin, 1996. "A note on the weak form efficiency of capital markets: The application of simple technical trading rules to UK stock prices - 1935 to 1994," Journal of Banking & Finance, Elsevier, vol. 20(6), pages 1121-1132, July.
    2. Ratner, Mitchell & Leal, Ricardo P. C., 1999. "Tests of technical trading strategies in the emerging equity markets of Latin America and Asia," Journal of Banking & Finance, Elsevier, vol. 23(12), pages 1887-1905, December.
    3. Pesaran, M Hashem & Timmermann, Allan, 2000. "A Recursive Modelling Approach to Predicting UK Stock Returns," Economic Journal, Royal Economic Society, vol. 110(460), pages 159-191, January.
    4. Dickey, David A & Fuller, Wayne A, 1981. "Likelihood Ratio Statistics for Autoregressive Time Series with a Unit Root," Econometrica, Econometric Society, vol. 49(4), pages 1057-1072, June.
    5. Pesaran, M Hashem & Timmermann, Allan, 1992. "A Simple Nonparametric Test of Predictive Performance," Journal of Business & Economic Statistics, American Statistical Association, vol. 10(4), pages 561-565, October.
    6. Pesaran, M Hashem & Timmermann, Allan, 1995. "Predictability of Stock Returns: Robustness and Economic Significance," Journal of Finance, American Finance Association, vol. 50(4), pages 1201-1228, September.
    7. Bessembinder, Hendrik & Chan, Kalok, 1995. "The profitability of technical trading rules in the Asian stock markets," Pacific-Basin Finance Journal, Elsevier, vol. 3(2-3), pages 257-284, July.
    8. Clare, A D & Thomas, S H & Wickens, M R, 1994. "Is the Gilt-Equity Yield Ratio Useful for Predicting UK Stock Returns?," Economic Journal, Royal Economic Society, vol. 104(423), pages 303-315, March.
    9. Kang, Joseph & Liu, Ming-Hua & Ni, Sophie Xiaoyan, 2002. "Contrarian and momentum strategies in the China stock market: 1993-2000," Pacific-Basin Finance Journal, Elsevier, vol. 10(3), pages 243-265, June.
    10. James Laurenceson & Joseph C.H. Chai, 2003. "Financial Reform and Economic Development in China," Books, Edward Elgar Publishing, number 2714.
    11. Gunasekarage, Abeyratna & Power, David M., 2001. "The profitability of moving average trading rules in South Asian stock markets," Emerging Markets Review, Elsevier, vol. 2(1), pages 17-33, March.
    12. Brock, William & Lakonishok, Josef & LeBaron, Blake, 1992. "Simple Technical Trading Rules and the Stochastic Properties of Stock Returns," Journal of Finance, American Finance Association, vol. 47(5), pages 1731-1764, December.
    13. Fama, Eugene F, 1991. "Efficient Capital Markets: II," Journal of Finance, American Finance Association, vol. 46(5), pages 1575-1617, December.
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    2. Onali, Enrico & Goddard, John, 2009. "Unifractality and multifractality in the Italian stock market," International Review of Financial Analysis, Elsevier, vol. 18(4), pages 154-163, September.

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