Testing the Weak Form Efficiency of Shanghai Stock Exchange with Artificial Neural Networks - Wong, Tai-chi Alick (2007)
The efficiency of a market has been a longstanding topic for research. On one side, researchers have provided numerous empirical studies in supporting the market efficiency; on the other side, market participants have been searching for new techniques for the prediction the market and applying various rules in trading, aiming to beat the market. Artificial neural networks (ANNs), being one of the artificial intelligence (A.I.) methodologies, have become one of the many options for the stock market predictions. Many researches have shown the capability of the ANNs in forecasting with nonlinear function mapping. The objective of this study is to verify the weak form efficiency of one of the emerging stock market, the Shanghai stock exchange, with the use of artificial neural networks. Simultaneously, an overview of the efficient market hypothesis and the former literatures regarding the development and the application of ANNs would be visited in order to provide a theoretical background for the study.