Buying and Selling Stocks of Multi Brands using Genetic Network Programming with control nodes

摘要

A new evolutionary method named "Genetic Network Programming with control nodes, GNPcn" has been proposed. GNPcn represents its solutions as directed graph structures which have some useful features inherently. For example, GNPcn has the implicit memory function which memorizes the past action sequences of agents and GNPcn can re-use nodes repeatedly in the network flow, so very compact graph structures can be made. GNPcn can improve the strategy of buying and selling stocks of multi brands. In this paper, buying and selling stocks of multi brands using GNPcn has been proposed, and its effectiveness is confirmed by simulations.