Automated Trading Signals based on Genetic Algorithm and Technical Analysis for Thai Index

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มนฤทัย ระดีรมย์์


- The proposed system in this research can decide a trading strategy for each day and produce a high profit for each stock. Decision trading support model is used to capture the knowledge in technical indicators for making decisions such as buy, hold and sell. The system consists of two stages: elimination of unacceptable stocks and stock trading construction. On the first stage, the proposed approach selected 15 stocks that publicly traded in the Thai Stock Exchange 100 Index (SET 100) from the year 2014 through 2015. On second stage, the experimental results have shown Annual Sharpe Ratio and Return Profits higher than “Buy & Hold” models for each stock index, and the models that used a Genetic Algorithm to optimizing a trading signal has profit better than another models. Especially TS17 as GA model, Annual Sharpe Ratio of Training set was 0.54, and Return Profit for 422 trading day was 23.2%. In Testing set, Annual Sharpe Ratio of Training set was 1.54, and Return Profit for 66 trading day was 9.52%. The results are very encouraging and can be implemented to increase the efficiency of a Decision-Trading System during the trading day.


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How to Cite
ระดีรมย์์ม., “Automated Trading Signals based on Genetic Algorithm and Technical Analysis for Thai Index”, JIST, vol. 5, no. 2, pp. 17-24, Dec. 2015.
Research Article: Soft Computing (Detail in Scope of Journal)


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