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Metaheuristics for the Index Tracking Problem

In: Metaheuristics in the Service Industry

Author

Listed:
  • Giacomo di Tollo

    (University of Basel)

  • Dietmar Maringer

    (University of Basel)

Abstract

Passive portfolio management strategies such as Index Tracking have gained considerable attention the industry recently which has also sparked some research interest. Index Tracking Problems are often complex in nature because of constraints on the portfolio structure and the chosen measure for the Tracking Error, quickly defying the use of traditional deterministic methods. Heuristic search and optimizationmethods, on the other hand, can dealwith this complexity and therefore appear as ideal choice to solve this class of problems. This contribution describes the Index Tracking Problem together with typical constraint encountered in practice, and illustrates how metaheuristic methods can be employed.

Suggested Citation

  • Giacomo di Tollo & Dietmar Maringer, 2009. "Metaheuristics for the Index Tracking Problem," Lecture Notes in Economics and Mathematical Systems, in: Kenneth Sörensen & Marc Sevaux & Walter Habenicht & Martin Josef Geiger (ed.), Metaheuristics in the Service Industry, chapter 8, pages 127-154, Springer.
  • Handle: RePEc:spr:lnechp:978-3-642-00939-6_8
    DOI: 10.1007/978-3-642-00939-6_8
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    Citations

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    Cited by:

    1. Mahdi Moeini, 2022. "Solving the index tracking problem: a continuous optimization approach," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 30(2), pages 807-835, June.
    2. Doering, Jana & Kizys, Renatas & Juan, Angel A. & Fitó, Àngels & Polat, Onur, 2019. "Metaheuristics for rich portfolio optimisation and risk management: Current state and future trends," Operations Research Perspectives, Elsevier, vol. 6(C).
    3. Filippi, C. & Guastaroba, G. & Speranza, M.G., 2016. "A heuristic framework for the bi-objective enhanced index tracking problem," Omega, Elsevier, vol. 65(C), pages 122-137.
    4. Jin Zhang & Dietmar Maringer, 2010. "Index Mutual Fund Replication," Working Papers 035, COMISEF.
    5. H Mezali & J E Beasley, 2013. "Quantile regression for index tracking and enhanced indexation," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 64(11), pages 1676-1692, November.

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