01-11-2014, 10:05 AM
Abstracts: Financial market is a complex, nonstationary, noisy, nonlinear and dynamic system but it does not follow random walk process. There are many factors that may cause the fluctuation of financial market movement. The main factors include economic condition, political situation, traders’ expectations, catastrophes and other unexpected events. Therefore, predictions of stock market price and its direction are quite difficult. In response to such difficulty, data mining (or machine learning) techniques have been introduced and applied for this financial prediction. Most of the studies have focused on the accurate forecasting of the value of stock price. However, different investors adopt different trading strategies; therefore, the forecasting model based on minimizing the error between the actual values and the forecasts may not be suitable for them. Instead, accurate prediction of movement direction of stock index is crucial for them to make effective market trading strategies. Some recent studies have suggested that trading strategies illustrated by the forecasts based on the direction of stock price change may be more effective and generate higher profit. Specifically, investors could effectively hedge against potential market risk and speculators as well as arbitrageurs could have opportunity of making profit by trading stock index whenever they could obtain the accurate prediction of stock price direction