Abstract:
In stock market, a technical trading rule is a popular tool for analysts and users to
do 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.
