Abstract
Stock investment has become an important investment activity in Thailand. However, investors often lose money due to unclear investment objectives. Therefore, an investment decision support system to assist investors in making good decisions has become an important research issue. Thus, this paper introduces an intelligent decision-making model, based on the application of Neurofuzzy system (NFs) technology. Our proposed system can decide a trading strategy for each day and produce a high profit for of each stock. Our decision-making model is used to capture the knowledge in technical indicators for making decisions such as buy, hold and sell. Finally, the experimental results have shown higher profits than the Neural Network (NN) and “Buy & Hold” models for each stock index. The results are very encouraging and can be implemented in a Decision- Trading System during the trading day.
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Radeerom, M., Wongsuwarn, H., Kasemsan, M.L.K. (2011). Intelligence Trading System for Thai Stock Index. In: Nguyen, N.T., Trawiński, B., Jung, J.J. (eds) New Challenges for Intelligent Information and Database Systems. Studies in Computational Intelligence, vol 351. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-19953-0_13
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DOI: https://doi.org/10.1007/978-3-642-19953-0_13
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