Trading rules on stock markets using genetic network programming with subroutines
Jianhua Li, QinBiao Meng, Yang Yang, Shingo Mabu, Yifei Wang, Kotaro Hirasawa · Society of Instrument and Control Engineers of Japan · 2010
The purpose of this paper is to enhance the performance of Genetic Network Programming (GNP) to be used for creating trading rules on stocks, where a new method named GNP with Subroutines has been proposed. Compared to the conversional GNP, a new kind of node named subroutines node is added, which can call subprograms (subroutines) from GNP main programs. This reusable subroutines, which has judgment nodes and processing nodes working like small scale GNP, can evolve concurrently during the evolution of main GNP. In the simulations, the stock prices of different brands from 2001 to 2004 are used to test the effectiveness of the proposed method.