Intelligence decision trading systems for stock index

Authors:
Monruthai Radeerom;Hataitep Wongsuwarn;M. L. Kulthon Kasemsan
Affiliations:
Faculty of Information Technology, Rangsit University, Pathumtani, Thailand;ME, Faculty of Engineering, Kasetsart University (Kamphaeng Saen), Nakhonpathom, Thailand;Faculty of Information Technology, Rangsit University, Pathumtani, Thailand
Venue:
ACIIDS'12 Proceedings of the 4th Asian conference on Intelligent Information and Database Systems - Volume Part III
Year:
2012

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Abstract

This paper introduces an intelligent decision-making model, based on the application of Fuzzy Logic and Neurofuzzy system (NFs) technology. Our proposed system can decide a trading strategy for each day and produce a high profit for each stock. Our decision-making model is used to capture the knowledge in technical indicators for making decisions such as buy, hold and sell. Moreover, we compared with 3 our proposed scenario of Intelligence Trading System model. Finally, the experimental results have shown higher profits than the Neural Network (NN) and "Buy & Hold" models for each stock index. And, some models which were including volume indicator and predicted close price on next day have profit batter than other models. The results are very encouraging and can be implemented in a Decision- Trading System during the trading day.