Varying portfolio construction of stocks using genetic network programming with control nodes

A new evolutionary method named “Genetic Network Programming with Control Nodes, GNPcn” has been proposed and applied to determine the timing of buying and selling stocks. GNPcn represents its solution as a directed graph structure which has 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 highly compact graph structures can be made. GNPcn can improve the strategy of buying and selling stocks of multi issues. Its effectiveness is confirmed by some simulations. Categories and Subject Descriptors J.1 [Computer Applications]: Administrative Data Processing General Terms Algorithms Keywords Genetic Network Programming, evolutionary computation, Candlestick Chart, buying and selling stocks.

• Type: Conference
• Year: 2008
• Where: GECCO
• Authors: Etsushi Ohkawa, Yan Chen, Shingo Mabu, Kaoru Shimada, Kotaro Hirasawa
• Keywords: Directed Graph Structure, GECCO 2008, Genetic Network Programming, Graph Structures, Optimization