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

31 Pages Posted: 4 Oct 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 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.

Keywords: random walk hypothesis, Chinese stock market, artificial neural network

JEL Classification: G14, F47

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=285715 or http://dx.doi.org/10.2139/ssrn.285715

Ali F. Darrat

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 (Contact Author)

University of Queensland - Business School ( email )

Brisbane, Queensland 4072
Australia

Do you have a job opening that you would like to promote on SSRN?

Paper statistics

Downloads
1,286
Abstract Views
5,449
rank
18,757
PlumX Metrics