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The Portfolio Heuristic Optimisation System (PHOS)

Author

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  • N. Loukeris

    (University of Macedonia)

  • I. Eleftheriadis

    (University of Macedonia)

  • E. Livanis

    (University of Macedonia)

Abstract

The efficient representation of the accurate corporate value on the stock price is vital to investors and fund managers that desire to optimise the net worth of the overall stock portfolio. Although the efficient market hypothesis sets limits, the practice of markets is an ideal place of manipulation, and corruption on prices. The accounting statements, evaluated by support vector machines and the SVM hybrids under genetic algorithms provide superiority in portfolio selection, on condition. A specific genetic hybrid SVM outperformed all examined SVM models being a powerful tool in financial analysis. We also offer the integrated model of portfolio selection, PHOS.

Suggested Citation

  • N. Loukeris & I. Eleftheriadis & E. Livanis, 2016. "The Portfolio Heuristic Optimisation System (PHOS)," Computational Economics, Springer;Society for Computational Economics, vol. 48(4), pages 627-648, December.
    • Handle: RePEc:kap:compec:v:48:y:2016:i:4:d:10.1007_s10614-015-9552-1
    DOI: 10.1007/s10614-015-9552-1
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    References listed on IDEAS

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    Cited by:

    1. Stelios Bekiros & Nikolaos Loukeris & Nikolaos Matsatsinis & Frank Bezzina, 2019. "Customer Satisfaction Prediction in the Shipping Industry with Hybrid Meta-heuristic Approaches," Computational Economics, Springer;Society for Computational Economics, vol. 54(2), pages 647-667, August.

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