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Index tracking with controlled number of assets using a hybrid heuristic combining genetic algorithm and non-linear programming

  • S.I. : CLAIO 2014
  • Published:
Annals of Operations Research Aims and scope Submit manuscript

Abstract

In this paper, we discuss the index tracking strategy using mathematical programming. First, we use a non-linear programming formulation for the index tracking problem, considering a limited number of assets. Since the problem is difficult to be solved in reasonable time by commercial mathematical packages, we apply a hybrid solution approach, combining mathematical programming and genetic algorithm. We show the efficiency of the proposed approach comparing the results with optimal solutions, with previous developed methods, and from real-world market indexes. The computational experiments focus on Ibovespa (the most important Brazilian market index), but we also present results for consolidated markets such as S&P 100 (USA), FTSE 100 (UK) and DAX (Germany). The proposed framework shows its ability to obtain very good results (gaps from the optimal solution smaller than 5 % in 8 min of CPU time) even for a highly volatile index from a developing country.

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Notes

  1. Newspaper: Valor Economico, August 2013: http://www.valor.com.br/financas/3235752/ogx-e-acao-que-mais-ganha-peso-na-nova-carteira-do-ibovespa.

  2. https://www.dropbox.com/s/ws1t6gorp4cvwkx/idx_tracking.zip?dl=0.

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Acknowledgments

The authors thank the two anonymous referees and the associate editor for their valuable comments and suggestions that greatly improved the quality of the paper. This research was funded by the following Brazilian Research Agencies: CAPES, CNPq, and FAPERGS; and Senescyt, Ecuador.

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Authors and Affiliations

  1. School of Business, Federal University of Rio Grande do Sul, 855 Washington Luiz Street, Porto, Alegre, Brazil

    Leonardo Riegel Sant’Anna, Tiago Pascoal Filomena, Pablo Cristini Guedes & Denis Borenstein

  2. Prometeo Researcher, Faculdad de Ciencias Económicas y Administrativas, Universidad de Cuenca, Cuenca, Ecuador

    Denis Borenstein

Authors
  1. Leonardo Riegel Sant’Anna
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  2. Tiago Pascoal Filomena
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  3. Pablo Cristini Guedes
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  4. Denis Borenstein
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Correspondence to Leonardo Riegel Sant’Anna.

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Sant’Anna, L.R., Filomena, T.P., Guedes, P.C. et al. Index tracking with controlled number of assets using a hybrid heuristic combining genetic algorithm and non-linear programming. Ann Oper Res 258, 849–867 (2017). https://doi.org/10.1007/s10479-016-2111-x

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  • DOI: https://doi.org/10.1007/s10479-016-2111-x

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