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International Conference on Hybrid Artificial Intelligence Systems

HAIS 2017: Hybrid Artificial Intelligent Systems pp 161–172Cite as

A Novel Hybrid Nature-Inspired Scheme for Solving a Financial Optimization Problem

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 10334))

Abstract

Hybrid intelligent approaches have proven their potential in demanding problem settings. The financial domain provides some challenging problem set-ups, mostly because of non-linearity conditions and conflicting objectives and binding restrictions. In this study, a novel hybrid algorithm, which stems from Nature-Inspired Intelligence, is applied in a specific portfolio optimization problem. The proposed algorithm comprises of an Ant Colony Optimization Algorithm (ACO) for detecting optimal combination of assets and a Gravitational Search Algorithm (GSA), for optimal capital allocation in the portfolio. Results from the proposed hybrid scheme are compared to previous findings, in the same optimization problem and dataset, from another hybrid NII algorithm, namely ACO Algorithm with Firefly Algorithm (FA). Experimental findings indicate that the proposed hybrid scheme yields a promising distribution of fitness values from independent simulation runs. What is more, in terms of best solution found, the proposed hybrid scheme yielded a solution that is 7.2% worst than the benchmark approach’s one. However, in terms of execution time, the proposed algorithm was faster. Taking into consideration both the above aspects, the difference of the two hybrid algorithms, in terms of best solution, can be characterized as insignificant. The main aim of the paper is to highlight the advantages of the proposed hybrid scheme, as well as the great potential of Nature-Inspired Intelligent algorithms for the financial portfolio optimization problem.

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References

  1. Maringer, D.: Portfolio Management with Heuristic Optimization. Advances in Computational Science. Springer, Heidelberg (2005)

    MATH  Google Scholar 

  2. Vassiliadis, V., Dounias, G.: Nature-inspired intelligence: a review of selected methods and applications. Int. J. Artif. Intell. Tools 18(4), 487–516 (2009)

    Article  Google Scholar 

  3. Giannakouris, G., Vassiliadis, V., Dounias, G.: Experimental study on a hybrid nature-inspired algorithm for financial portfolio optimization. In: Konstantopoulos, S., Perantonis, S., Karkaletsis, V., Spyropoulos, Constantine D., Vouros, G. (eds.) SETN 2010. LNCS, vol. 6040, pp. 101–111. Springer, Heidelberg (2010). doi:10.1007/978-3-642-12842-4_14

    Chapter  Google Scholar 

  4. Shapcott, J.: Index tracking: genetic algorithms for investment portfolio selection. EPCC-SS92-24, pp. 1–24 (1992)

    Google Scholar 

  5. Gomez, M. A., Flores, C.X., Osorio, M.A.: Hybrid search for cardinality constrained portfolio optimization. In: GECCO 2006, pp. 1865–1866 (2006)

    Google Scholar 

  6. Markowitz, H.: Portfolio selection. J. Finan. 7(1), 77–91 (1952)

    Google Scholar 

  7. Vassiliadis, V., Thomaidis, N., Dounias, G.: Active portfolio management under a downside risk framework: comparison of a hybrid nature – inspired scheme. In: Corchado, E., Wu, X., Oja, E., Herrero, Á., Baruque, B. (eds.) HAIS 2009. LNCS, vol. 5572, pp. 702–712. Springer, Heidelberg (2009). doi:10.1007/978-3-642-02319-4_85

    Chapter  Google Scholar 

  8. Chen, W., Zhang, R.T., Cai, Y.M., Xu, F.S.: Particle swarm optimization for constrained portfolio selection problems. In: 5th International Conference on Machine Learning and Cybernetics, pp. 2425–2429 (2006)

    Google Scholar 

  9. Thomaidis, N.S., Angelidis, T., Vassiliadis, V., Dounias, G.: Active portfolio management with cardinality constraints: an application of particle swarm optimization. New Math. Nat. Comput. 5(03), 535–555 (2009)

    Article  MATH  Google Scholar 

  10. Dorigo, M., Stultze, M.: Ant Colony Optimization. The MIT Press, Cambridge (2004)

    MATH  Google Scholar 

  11. Yang, X.S.: Nature-Inspired Metaheuristic Algorithm. Luniver Press, Bristol (2008)

    Google Scholar 

  12. Rashedi, E., Nezamabadi-Pour, H., Saryazdi, S.: GSA: a gravitational search algorithm. Inf. Sci. 179(13), 2232–2248 (2009)

    Article  MATH  Google Scholar 

  13. Xing, B., Gao, W.-J.: Gravitational search algorithm. In: Xing, B., Gao, W.-J. (eds.) Innovative Computational Intelligence: A Rough Guide to 134 Clever Algorithms. ISRL, vol. 62, pp. 355–364. Springer, Cham (2014). doi:10.1007/978-3-319-03404-1_22

    Chapter  Google Scholar 

  14. Sabri, N.M., Puteh, M., Mahmood, M.R.: A review of gravitational search algorithm. Int. J. Adv. Soft Comput. Appl. 5(3), 1–39 (2013)

    Google Scholar 

  15. Kuhn, J.: Optimal Risk-Return Tradeoffs of Commercial Banks and the Suitability of Profitability Measures for Loan Portfolios. Springer, Berlin (2006)

    MATH  Google Scholar 

  16. Sharpe, W.F.: The sharpe ratio. J. Portfolio Manage. 21(1), 49–58 (1994)

    Article  Google Scholar 

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Author information

Authors and Affiliations

  1. Management and Decision Engineering Laboratory, Department of Financial and Management Engineering, University of the Aegean, 41 Kountouriotou Str., 82100, Chios, Greece

    Alexandros Tzanetos, Vassilios Vassiliadis & Georgios Dounias

Authors
  1. Alexandros Tzanetos
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  2. Vassilios Vassiliadis
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  3. Georgios Dounias
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Corresponding author

Correspondence to Vassilios Vassiliadis .

Editor information

Editors and Affiliations

  1. University of La Rioja , Logroño, La Rioja, Spain

    Francisco Javier Martínez de Pisón

  2. University of La Rioja , Logroño, La Rioja, Spain

    Rubén Urraca

  3. University of A Coruña , Ferrol, La Coruña, Spain

    Héctor Quintián

  4. University of Salamanca, Salamanca, Spain

    Emilio Corchado

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Tzanetos, A., Vassiliadis, V., Dounias, G. (2017). A Novel Hybrid Nature-Inspired Scheme for Solving a Financial Optimization Problem. In: Martínez de Pisón, F., Urraca, R., Quintián, H., Corchado, E. (eds) Hybrid Artificial Intelligent Systems. HAIS 2017. Lecture Notes in Computer Science(), vol 10334. Springer, Cham. https://doi.org/10.1007/978-3-319-59650-1_14

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  • DOI: https://doi.org/10.1007/978-3-319-59650-1_14

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-59649-5

  • Online ISBN: 978-3-319-59650-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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