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

Yan Chen, Shingo Mabu, Kotaro Hirasawa, Takayuki Furuzuki

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)

Abstract

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.

Original languageEnglish
Title of host publicationProceedings of GECCO 2007: Genetic and Evolutionary Computation Conference
Pages1503
Number of pages1
DOIs
Publication statusPublished - 2007
Event9th Annual Genetic and Evolutionary Computation Conference, GECCO 2007 - London
Duration: 2007 Jul 72007 Jul 11

Other

Other9th Annual Genetic and Evolutionary Computation Conference, GECCO 2007
CityLondon
Period07/7/707/7/11

Fingerprint

Network Programming
Genetic Network
Reinforcement learning
Stock Market
Genetic Programming
Sales
Evolutionary algorithms
Stock Prices
Learning algorithms
Profitability
Data storage equipment
Reinforcement Learning
Implicit Function
Memory Function
Evolutionary Computation
Vertex of a graph
Dynamic Environment
Learning
Financial markets
Chart

Keywords

  • Candlestick chart
  • Genetic network programming
  • Reinforcement learning
  • Sarsa
  • Stock trading model
  • Technical index

ASJC Scopus subject areas

  • Artificial Intelligence
  • Software
  • Theoretical Computer Science

Cite this

Chen, Y., Mabu, S., Hirasawa, K., & Furuzuki, T. (2007). Trading rules on stock markets using genetic network programming with sarsa learning. In Proceedings of GECCO 2007: Genetic and Evolutionary Computation Conference (pp. 1503) https://doi.org/10.1145/1276958.1277232

Trading rules on stock markets using genetic network programming with sarsa learning. / Chen, Yan; Mabu, Shingo; Hirasawa, Kotaro; Furuzuki, Takayuki.

Proceedings of GECCO 2007: Genetic and Evolutionary Computation Conference. 2007. p. 1503.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Chen, Y, Mabu, S, Hirasawa, K & Furuzuki, T 2007, Trading rules on stock markets using genetic network programming with sarsa learning. in Proceedings of GECCO 2007: Genetic and Evolutionary Computation Conference. pp. 1503, 9th Annual Genetic and Evolutionary Computation Conference, GECCO 2007, London, 07/7/7. https://doi.org/10.1145/1276958.1277232
Chen Y, Mabu S, Hirasawa K, Furuzuki T. Trading rules on stock markets using genetic network programming with sarsa learning. In Proceedings of GECCO 2007: Genetic and Evolutionary Computation Conference. 2007. p. 1503 https://doi.org/10.1145/1276958.1277232
Chen, Yan ; Mabu, Shingo ; Hirasawa, Kotaro ; Furuzuki, Takayuki. / Trading rules on stock markets using genetic network programming with sarsa learning. Proceedings of GECCO 2007: Genetic and Evolutionary Computation Conference. 2007. pp. 1503
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