Stock investment decision making based on quantitative association rules

As stock market investing attracts many investors to get a profit, trend and stock price forecasting plays an important role in the stock market. Many professional traders use the technical analysis to analyze the stocks and predict the stock price. Candlestick chart analysis is one of the technical analyses which is widely used for investment decision making. Quantitative association rule mining is a rule mining method that considers the quantitative attributes which contain richer information than the Boolean or categorical attributes. The data used in this research is stock prices of 38 companies which are listed in Taiwan 50 index from January 5th 1999 until February 27th 2014. In this research, stock price change is predicted and the quantitative association rules are generated using the trade volume, 5-day and 10-day moving average, price range, 1-day candlestick pattern, and price change on the next day and the next fifth day. Based on the rules generated and the buying and selling decisions, there is more than 335% profit which can be gained. © 2015 ICIC International.