Buying and Selling Stocks of Multi Brands Using Genetic Network Programming with Control Nodes

  • Ohkawa Etsushi
    Graduate School of Information, Production and Systems, Waseda University
  • Chen Yan
    Graduate School of Information, Production and Systems, Waseda University
  • Bao Zhiguo
    Graduate School of Information, Production and Systems, Waseda University
  • Mabu Shingo
    Graduate School of Information, Production and Systems, Waseda University
  • Shimada Kaoru
    Information, Production and Systems Research Center, Waseda University
  • Hirasawa Kotaro
    Graduate School of Information, Production and Systems, Waseda University

この論文をさがす

抄録

A new evolutionary method named “Genetic Network Programming with control nodes, GNPcn” has been applied to determine the timing of buying or selling stocks. GNPcn represents its solutions as directed graph structures which has some useful features inherently. For example, GNPcn has an 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 determine the strategy of buying and selling stocks of multi issues. The effectiveness of the proposed method is confirmed by simulations.

収録刊行物

被引用文献 (1)*注記

もっと見る

参考文献 (22)*注記

もっと見る

詳細情報 詳細情報について

問題の指摘

ページトップへ