The applications of genetic algorithms in stock market data mining optimisation

Publication Type:
Conference Proceeding
Management Information Systems, 2004, 10 pp. 273 - 280
Issue Date:
Full metadata record
In the stock market, a technical trading rule is a popular tool for analysts and users to carry out their research and decide to buy or sell their shares. The key issue for the success of a trading rule is the selection of values for all parameters and their combinations. However, the range of parameters can vary in a large domain, so it is difficult for users to find the best parameter combination. In this paper, we present the Genetic Algorithm (GA) to overcome the problem in two steps: first, setting a sub-domain of the parameters with GA; second, finding a near optimal value in the sub domain with GA in a very reasonable time.
Please use this identifier to cite or link to this item: