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On Testing the Random-Walk Hypothesis: A Model-Comparison Approach

Listed author(s):
  • Darrat, Ali F
  • Zhong, Maosen
Registered author(s):

    The main intention of this paper is to investigate, with new daily data, whether prices in the two Chinese stock exchanges (Shanghai and Shenzhen) follow a random-walk process as required by market efficiency. We use two different approaches, the standard variance-ratio test of Lo and MacKinlay (1988) and a model-comparison test that compares the ex post forecasts from a NAIVE model with those obtained from several alternative models: ARIMA, GARCH and the Artificial Neural Network (ANN). To evaluate ex post forecasts, we utilize several procedures including RMSE, MAE, Theil's U, and encompassing tests. In contrast to the variance-ratio test, results from the model-comparison approach are quite decisive in rejecting the random-walk hypothesis in both Chinese stock markets. Moreover, our results provide strong support for the ANN as a potentially useful device for predicting stock prices in emerging markets. Copyright 2000 by MIT Press.

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    Article provided by Eastern Finance Association in its journal The Financial Review.

    Volume (Year): 35 (2000)
    Issue (Month): 3 (August)
    Pages: 105-124

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    Handle: RePEc:bla:finrev:v:35:y:2000:i:3:p:105-24
    Contact details of provider: Web page: http://www.easternfinance.org/

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