IntroductionIn past, the pursuits for predicting stock price mostly used time series like Auto Regression Integrated Moving Average (ARIMA) or the neural network models like Back Propagation Neural Network (BPN). Generally, these models have two common features in the selection of input factors: (1) the emphasis of the quantitative indices, (2) the requirement of large amount of input data. Nevertheless, these quantitative indices are not really suitable for the financial market. Furthemore, the requirement of large amount of input data will lower down the convergent rate of neural network model. Such that, this research attempts to develop a better prediction model by the integration of neural network technique and grey theory for the SIMEX Taiwan stock index future.In this research, the grey theory applied include grey forecast model and grey relationship analysis. The grey forecast model, GM(l,l), was applied to predict the next day's stock index future. To examine the influence of dimension of the model to prediction accuracy, seven different kinds of dimension 5, 6, 8, 10, 12, 14, and 15 were tested. The generated data were then regarded as new technical indices in grey relationship analysis and prediction of neural network. Grey relationship analysis was used to filter the most important quantitative technical indices.Finally, a Recurrent Neural Network was developed to train and predict the price trend of stock index future. In the network structure, the price trend of stock index future as the output and the values gained from previous processing in grey relationship analysis as the input. The conclusion shows our models can provide good prediction for this problem.Is stock price really predicable? In the earlier stage, under the assumption of efficient market investors believed that the movement of stock price presents a state of random walk. That means it is impossible to predict the change of stock price by its historical data. Nevertheless, some researchers who did empirical studies applying investment portfolio found historical information is actually usell in prediction [l].As the description above about the uncertainty of price movement, therefore, it is understandable that investment risk of stock is not low. In the traditional theory of investment portfolio, risk of stock can be divided into systematic risk and unsystematic risk. Systematic risk causes reward change of the whole market on a single stock. Mostly, it is originated by the changes of politics, society, and whole economic environment. For instance, the Asia financial crisis fiom the end of 1997 had caused the stock markets in Southeastem Asia and Eastern Asia drastically dropped off. This kind of risk is usually not easy to avoid through investment portfolio. Therefore, it is also called market risk or unavoidable risk. However, Unsystematic risk is determined by the fluctuation of stock reward ratio which is influenced by circulation volume of stock, supply and demand of stock, and management performance of the enterprise. Hence, thi...
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