Buying and selling stocks of multi brands using genetic network programming with control nodes

Zhiguo Bao; Shigo Mabu; Kotaro Hirasawa; Jinglu Hu

doi:10.1109/SICE.2007.4421233

Buying and selling stocks of multi brands using genetic network programming with control nodes

Zhiguo Bao^*, Shigo Mabu, Kotaro Hirasawa, Jinglu Hu

^*Corresponding author for this work

Graduate School of Information, Production and Systems

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

2 Citations (Scopus)

Abstract

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.

Original language	English
Title of host publication	SICE Annual Conference, SICE 2007
Pages	1569-1576
Number of pages	8
DOIs	https://doi.org/10.1109/SICE.2007.4421233
Publication status	Published - 2007
Event	SICE(Society of Instrument and Control Engineers)Annual Conference, SICE 2007 - Takamatsu, Japan Duration: 2007 Sept 17 → 2007 Sept 20

Publication series

Name	Proceedings of the SICE Annual Conference

Conference

Conference	SICE(Society of Instrument and Control Engineers)Annual Conference, SICE 2007
Country/Territory	Japan
City	Takamatsu
Period	07/9/17 → 07/9/20

Keywords

Buying and selling stocks
Candlestick chart
Evolutionary computation
Genetic network programming

ASJC Scopus subject areas

Control and Systems Engineering
Computer Science Applications
Electrical and Electronic Engineering

Access to Document

10.1109/SICE.2007.4421233

Cite this

Bao, Z, Mabu, S, Hirasawa, K & Hu, J 2007, Buying and selling stocks of multi brands using genetic network programming with control nodes. in SICE Annual Conference, SICE 2007., 4421233, Proceedings of the SICE Annual Conference, pp. 1569-1576, SICE(Society of Instrument and Control Engineers)Annual Conference, SICE 2007, Takamatsu, Japan, 07/9/17. https://doi.org/10.1109/SICE.2007.4421233

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title = "Buying and selling stocks of multi brands using genetic network programming with control nodes",

abstract = "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.",

keywords = "Buying and selling stocks, Candlestick chart, Evolutionary computation, Genetic network programming",

author = "Zhiguo Bao and Shigo Mabu and Kotaro Hirasawa and Jinglu Hu",

year = "2007",

doi = "10.1109/SICE.2007.4421233",

language = "English",

isbn = "4907764286",

series = "Proceedings of the SICE Annual Conference",

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AU - Bao, Zhiguo

AU - Mabu, Shigo

AU - Hirasawa, Kotaro

AU - Hu, Jinglu

PY - 2007

Y1 - 2007

N2 - 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.

AB - 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.

KW - Buying and selling stocks

KW - Candlestick chart

KW - Evolutionary computation

KW - Genetic network programming

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T3 - Proceedings of the SICE Annual Conference

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ER -

Buying and selling stocks of multi brands using genetic network programming with control nodes

Abstract

Publication series

Conference

Keywords

ASJC Scopus subject areas

Access to Document

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