Trading rules on stock markets using genetic network programming with sarsa learning

Yan Chen*, Shingo Mabu, Kotaro Hirasawa, Jinglu Hu


研究成果: Conference contribution

4 被引用数 (Scopus)


In this paper, the Genetic Network Programming (GNP) for creating trading rules on stocks is described. GNP is an evolutionary computation, which represents its solutions using graph structures and has some useful features inherently. It has been clarified that GNP works well especially in dynamic environments since GNP can create quite compact programs and has an implicit memory function. In this paper, GNP is applied to creating a stock trading model. There are three important points: The first important point is to combine GNP with Sarsa Learning which is one of the reinforcement learning algorithms. Evolution-based methods evolve their programs after task execution because they must calculate fitness values, while reinforcement learning can change programs during task execution, therefore the programs can be created efficiently. The second important point is that GNP uses candlestick chart and selects appropriate technical indices to judge the buying and selling timing of stocks. The third important point is that sub-nodes are used in each node to determine appropriate actions (buying/selling) and to select appropriate stock price information depending on the situation. In the simulations, the trading model is trained using the stock prices of 16 brands in 2001, 2002 and 2003. Then the generalization ability is tested using the stock prices in 2004. From the simulation results, it is clarified that the trading rules of the proposed method obtain much higher profits than Buy&Hold method and its effectiveness has been confirmed.

ホスト出版物のタイトルProceedings of GECCO 2007
ホスト出版物のサブタイトルGenetic and Evolutionary Computation Conference
出版ステータスPublished - 2007
イベント9th Annual Genetic and Evolutionary Computation Conference, GECCO 2007 - London, United Kingdom
継続期間: 2007 7月 72007 7月 11


名前Proceedings of GECCO 2007: Genetic and Evolutionary Computation Conference


Conference9th Annual Genetic and Evolutionary Computation Conference, GECCO 2007
国/地域United Kingdom

ASJC Scopus subject areas

  • 人工知能
  • ソフトウェア
  • 理論的コンピュータサイエンス


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