DocumentCode
2465282
Title
Trading Rules on the Stock Markets using Genetic Network Programming with Candlestick Chart
Author
Izumi, Yoshihiro ; Yamaguchi, Tokiyo ; Mabu, Shingo ; Hirasawa, Kotaro ; Hu, Jingle
Author_Institution
Waseda Univ., Fukuoka
fYear
0
fDate
0-0 0
Firstpage
2362
Lastpage
2367
Abstract
A new evolutionary method named "genetic network programming, GNP" has been proposed. GNP represents its solutions as directed graph structures which have some useful features inherently. For example, GNP has the implicit memory function which memorizes the past action sequences of agents, and GNP can re-use nodes repeatedly in the network flow, so very compact graph structures can be made. In this paper, buying/selling model for stock market using GNP with candlestick chart has been proposed and its effectiveness is confirmed by simulations.
Keywords
directed graphs; genetic algorithms; stock markets; buying/selling model; candlestick chart; directed graph structures; genetic network programming; implicit memory function; stock markets; trading rules; Computational modeling; Computer networks; Economic indicators; Educational institutions; Evolutionary computation; Fluctuations; Genetic algorithms; Genetic programming; Production systems; Stock markets;
fLanguage
English
Publisher
ieee
Conference_Titel
Evolutionary Computation, 2006. CEC 2006. IEEE Congress on
Conference_Location
Vancouver, BC
Print_ISBN
0-7803-9487-9
Type
conf
DOI
10.1109/CEC.2006.1688600
Filename
1688600
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