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

Posted: 15 Aug 2001

See all articles by Ali F. Darrat

Ali F. Darrat

Louisiana Tech University - College of Business

Maosen Zhong

University of Queensland - Business School

Multiple version iconThere are 3 versions of this paper

Abstract

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.

JEL Classification: G12, G14

Suggested Citation

Darrat, Ali F. and Zhong, Maosen, On Testing the Random-Walk Hypothesis: A Model-Comparison Approach. Available at SSRN: https://ssrn.com/abstract=237796

Ali F. Darrat (Contact Author)

Louisiana Tech University - College of Business ( email )

Department of Economics & Finance
P.O. Box 10318
Ruston, LA 71272
United States
318-257-3874 (Phone)
318-257-4253 (Fax)

Maosen Zhong

University of Queensland - Business School ( email )

Brisbane, Queensland 4072
Australia

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