Enhancement of 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

2 引用 (Scopus)

抜粋

In this paper, the enhancement of trading rules on stock markets using Genetic Network Programming (GNP) with Sarsa Learning is described. There are three important points in this paper: First, we use GNP with Sarsa learning as the basic algorithm while importance Indices and Candlestick Charts are introduced for efficient stock trading decision-making. Importance indices have been proposed to tell GNP the timing of buying and selling stocks. Second, to improve the performance of the proposed GNP-Sarsa algorithm, we develop a new method that can learn appropriate function describing the relation between the value of each technical index and the output of the importance index (IMX). This is an important point that devotes to the enhancement of the proposed GNP-Sarsa algorithm.Third, in order to create more efficient judgment functions to judge the current stock price appropriately, we develop a new way of classifying the candlestick chart body type. To confirm the effectiveness of the proposed method, we also compare the simulation results using GNP-Sarsa with other methods like traditional GNP and Buy&Hold method.

元の言語English
ホスト出版物のタイトルSICE Annual Conference, SICE 2007
ページ2700-2707
ページ数8
DOI
出版物ステータスPublished - 2007 12 1
イベントSICE(Society of Instrument and Control Engineers)Annual Conference, SICE 2007 - Takamatsu, Japan
継続期間: 2007 9 172007 9 20

出版物シリーズ

名前Proceedings of the SICE Annual Conference

Conference

ConferenceSICE(Society of Instrument and Control Engineers)Annual Conference, SICE 2007
Japan
Takamatsu
期間07/9/1707/9/20

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Computer Science Applications
  • Electrical and Electronic Engineering

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  • これを引用

    Chen, Y., Mabu, S., Hirasawa, K., & Hu, J. (2007). Enhancement of trading rules on stock markets using Genetic Network Programming with Sarsa Learning. : SICE Annual Conference, SICE 2007 (pp. 2700-2707). [4421448] (Proceedings of the SICE Annual Conference). https://doi.org/10.1109/SICE.2007.4421448