Incremental genetic fuzzy expert trading system for derivatives market timing

Technical indicators are normally used to monitor the stock prices and assist investors to set up trading rules to make the buy-sell-hold decision. Although some trading rules are clear, most of them are vague and fuzzy. Therefore, an investor cannot be the winner all the time with the same set of trading rules. The weight of trading rules should be varied with time. A Genetic Fuzzy Expert Trading System (GFETS) was designed to simulate the vague and fuzzy trading rules and give the buy-sell signal. Fuzzy trading rules are optimized and selected using genetic algorithm in GFETS. Experimental evaluations showed that trading with the optimized fuzzy trading rules obtains a good profitable return. To maintain the quality of the fuzzy trading rules being in-used, GFETS must be re-trained from time-to-time. In this paper, an incremental training approach was studied and evaluated with all Hang Seng China Enterprises Index (HSCEI) stocks. The risk and the profit return compared with other trading strategies were reported.