Integration of mutual information and CRPSO-based fuzzy model for stock index forecasting
Jungwon Yu, Sungshin Kim
Available Online June 2015.
- https://doi.org/10.2991/ifsa-eusflat-15.2015.89How to use a DOI?
- Stock index prediction, mamdani-type fuzzy model, mutual information, Sequential forward input selection, cooperative random learning particle swarm optimization (CRPSO).
- In this paper, the integration of mutual information (MI) and fuzzy model is proposed to predict stock indexes with complex and non-linear characteristics. Technical indicators are considered as initial input candidates and significant inputs are determined by MI-based input selection method. To identify the structures and parameters of fuzzy models simultaneously, cooperative random learning particle swarm optimization (CRPSO), proposed by Zhao et al., is used. To confirm the effectiveness, the proposed method and comparison methods are applied to the Korea Composite Stock Price Index (KOSPI). The experimental results show that the proposed method, on average, outperforms other comparison methods.
- Open Access
- This is an open access article distributed under the CC BY-NC license.
Cite this article
TY - CONF AU - Jungwon Yu AU - Sungshin Kim PY - 2015/06 DA - 2015/06 TI - Integration of mutual information and CRPSO-based fuzzy model for stock index forecasting BT - Proceedings of the 2015 Conference of the International Fuzzy Systems Association and the European Society for Fuzzy Logic and Technology PB - Atlantis Press SP - 624 EP - 631 SN - 1951-6851 UR - https://doi.org/10.2991/ifsa-eusflat-15.2015.89 DO - https://doi.org/10.2991/ifsa-eusflat-15.2015.89 ID - Yu2015/06 ER -