System Trading of Diversified Investment by Hybrid Method of GP and GA
Noriaki Koide, Koji Okuhara, Hiroshi Tsuda · Proceedings of the ISCIE International Symposium on Stochastic Systems Theory and its Applications · 2012
There are many types of Evolutionary Algorithm. Among them, Genetic Programming (GP) has the rich expression of solution for a lot of problems, and Genetic Algorithm (GA) is good for the tuning of parameters on 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 does not work well, we can decrease the risk with the diversified investment. In addition, to increase the success rate of searching and applying, we discuss about the hybrid algorithm of GP and GA, and we show its effectiveness in the extraction of investment rule. In numerical example, it is shown that our proposed model have better performance rathar than the usual models combining GA and GP.