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Complex-Valued Neural Network Model and Its Application to Stock Prediction

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Proceedings of the 16th International Conference on Hybrid Intelligent Systems (HIS 2016) (HIS 2016)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 552))

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Abstract

In this paper, a novel complex-valued neural network (CVNN) algorithm is proposed to predict stock index. In a CVNN, input layer, weights, threshold values and output layer are all complex numbers. Cuckoo search (CS) is proposed to optimize the complex parameters. NIFTY stock market indices and Shanghai stock exchange composite index are used to evaluate the performance of CVNN. The results reveal that CVNN performs better than the classical real neural networks.

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Acknowledgements

This study was funded by the Ph.D. research startup foundation of Zaozhuang University (No. 2014BS13), foundation of Zaozhuang University (2015YY02) and Shandong Provincial Natural Science Foundation, China (No. ZR2015PF007).

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Authors and Affiliations

  1. School of Information Science and Engineering, Zaozhuang University, Zaozhuang, 277160, China

    Haifeng Wang, Bin Yang & Jiaguo Lv

Authors
  1. Haifeng Wang
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  2. Bin Yang
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  3. Jiaguo Lv
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Corresponding author

Correspondence to Bin Yang .

Editor information

Editors and Affiliations

  1. (MIR Labs), Machine Intelligence Research Labs, Auburn, Washington, USA

    Ajith Abraham

  2. Hassan 1st University, Settat, Morocco

    Abdelkrim Haqiq

  3. ENIS, University of Sfax, Sfax, Tunisia

    Adel M. Alimi

  4. Technopolis Rabat-Shore Rocade, International University of Rabat, Sala el Jadida, Morocco

    Ghita Mezzour

  5. Inst Applied Dept of Electronics, Taffala, University of Sousse, Sousse, Tunisia

    Nizar Rokbani

  6. Fakulti Teknologi Maklumat dan Komunikas, Universiti Teknikal Malaysia Melaka, Durian Tunggal, Malaysia

    Azah Kamilah Muda

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Wang, H., Yang, B., Lv, J. (2017). Complex-Valued Neural Network Model and Its Application to Stock Prediction. In: Abraham, A., Haqiq, A., Alimi, A., Mezzour, G., Rokbani, N., Muda, A. (eds) Proceedings of the 16th International Conference on Hybrid Intelligent Systems (HIS 2016). HIS 2016. Advances in Intelligent Systems and Computing, vol 552. Springer, Cham. https://doi.org/10.1007/978-3-319-52941-7_3

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  • DOI: https://doi.org/10.1007/978-3-319-52941-7_3

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-52940-0

  • Online ISBN: 978-3-319-52941-7

  • eBook Packages: EngineeringEngineering (R0)

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