Extracting trading rules from the multiple classifiers and technical indicators in stock market
This study intends to mine reasonable trading rules by classifying the up/down fluctuant direction of the price for Korea Stock Price Index 200 (KOSPI 200) futures. This research consists of two stages. The first stage is classifying the fluctuant direction of the price for KOSPI 200 futures with several technical indicators using artificial intelligence techniques. And the second stage is mining the trading rules to resolute conflict among the outputs of the first stage using the inductive learning. To verify the effectiveness of proposed approach, this study composes four comparable models and performs statistical test. Experimental results show that the classification performance of the proposed model outperforms that of other comparable models. In addition, the proposed model yields higher profit than other comparable models and buy-and-hold strategy.