Stock Trading Using RSPOP: A Novel Rough Set-Based Neuro-Fuzzy Approach

@article{Ang2006StockTU,
  title={Stock Trading Using RSPOP: A Novel Rough Set-Based Neuro-Fuzzy Approach},
  author={Kai Keng Ang and Hiok Chai Quek},
  journal={IEEE Transactions on Neural Networks},
  year={2006},
  volume={17},
  pages={1301-1315}
}
This paper investigates the method of forecasting stock price difference on artificially generated price series data using neuro-fuzzy systems and neural networks. As trading profits is more important to an investor than statistical performance, this paper proposes a novel rough set-based neuro-fuzzy stock trading decision model called stock trading using rough set-based pseudo outer-product (RSPOP) which synergizes the price difference forecast method with a forecast bottleneck free trading… CONTINUE READING

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