Knowledge Discovery by Combination of Indexes for Signal Detection for Economic Time Series Data

抄録

There are many types of Evolutionary Algorithm. Genetic Programming has the rich expression of the solution for a lot of problems, and Genetic Algorithm is good for the tuning of parameters for the array. However, when we apply each of them to the extraction of investment rule, it needs a lot of searching for useful solution in the field of foreign exchange. So we introduce the diversified investment using multiple solutions, and even if the searching is not good, we can decrease the risk with the diversified investment. In the numerical example, we compare the proposed hybrid algorithm of Genetic Programming including Genetic Algorithm with the island model in the layer of Genetic Programming which are different 3 tournament sizes without migration. It is shown our model has higher performance to economic time series data rather than others. Furthermore, it can be shown that our model can detect signal by the combination of indexes as the knowledge discovery.