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A heuristic framework for the bi-objective enhanced index tracking problem

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  • Filippi, C.
  • Guastaroba, G.
  • Speranza, M.G.

Abstract

The index tracking problem is the problem of determining a portfolio of assets whose performance replicates, as closely as possible, that of a financial market index chosen as benchmark. In the enhanced index tracking problem the portfolio is expected to outperform the benchmark with minimal additional risk. In this paper, we study the bi-objective enhanced index tracking problem where two competing objectives, i.e., the expected excess return of the portfolio over the benchmark and the tracking error, are taken into consideration. A bi-objective Mixed Integer Linear Programming formulation for the problem is proposed. Computational results on a set of benchmark instances are given, along with a detailed out-of-sample analysis of the performance of the optimal portfolios selected by the proposed model. Then, a heuristic procedure is designed to build an approximation of the set of Pareto optimal solutions. We test the proposed procedure on a reference set of Pareto optimal solutions. Computational results show that the procedure is significantly faster than the exact computation and provides an extremely accurate approximation.

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  • 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.
  • Handle: RePEc:eee:jomega:v:65:y:2016:i:c:p:122-137
    DOI: 10.1016/j.omega.2016.01.004
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    Cited by:

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    3. Guastaroba, G. & Savelsbergh, M. & Speranza, M.G., 2017. "Adaptive Kernel Search: A heuristic for solving Mixed Integer linear Programs," European Journal of Operational Research, Elsevier, vol. 263(3), pages 789-804.
    4. Dimitris Andriosopoulos & Michalis Doumpos & Panos M. Pardalos & Constantin Zopounidis, 2019. "Computational approaches and data analytics in financial services: A literature review," Journal of the Operational Research Society, Taylor & Francis Journals, vol. 70(10), pages 1581-1599, October.
    5. Ruchika Sehgal & Aparna Mehra, 2023. "Quantile Regression Based Enhanced Indexing with Portfolio Rebalancing," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 21(3), pages 721-742, September.
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    10. Huang, Jinbo & Li, Yong & Yao, Haixiang, 2018. "Index tracking model, downside risk and non-parametric kernel estimation," Journal of Economic Dynamics and Control, Elsevier, vol. 92(C), pages 103-128.
    11. Strub, O. & Baumann, P., 2018. "Optimal construction and rebalancing of index-tracking portfolios," European Journal of Operational Research, Elsevier, vol. 264(1), pages 370-387.
    12. 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).
    13. Li, Xuepeng & Xu, Fengmin & Jing, Kui, 2022. "Robust enhanced indexation with ESG: An empirical study in the Chinese Stock Market," Economic Modelling, Elsevier, vol. 107(C).
    14. Huang, Jinbo & Li, Yong & Yao, Haixiang, 2022. "Partial moments and indexation investment strategies," Journal of Empirical Finance, Elsevier, vol. 67(C), pages 39-59.
    15. Gianfranco Guastaroba & Renata Mansini & Wlodzimierz Ogryczak & M. Grazia Speranza, 2020. "Enhanced index tracking with CVaR-based ratio measures," Annals of Operations Research, Springer, vol. 292(2), pages 883-931, September.
    16. F. Hooshmand & Z. Rasouli, 2023. "Enhanced index tracking problem: a new optimization model and a sum-of-ratio based algorithm," OPSEARCH, Springer;Operational Research Society of India, vol. 60(3), pages 1286-1311, September.
    17. Sant’Anna, Leonardo Riegel & Caldeira, João Frois & Filomena, Tiago Pascoal, 2020. "Lasso-based index tracking and statistical arbitrage long-short strategies," The North American Journal of Economics and Finance, Elsevier, vol. 51(C).
    18. Kinene, Alan & Birolini, Sebastian & Cattaneo, Mattia & Granberg, Tobias Andersson, 2023. "Electric aircraft charging network design for regional routes: A novel mathematical formulation and kernel search heuristic," European Journal of Operational Research, Elsevier, vol. 309(3), pages 1300-1315.
    19. Tingting Yang & Xiaoxia Huang, 2022. "A New Portfolio Optimization Model Under Tracking-Error Constraint with Linear Uncertainty Distributions," Journal of Optimization Theory and Applications, Springer, vol. 195(2), pages 723-747, November.
    20. Guastaroba, G. & Mansini, R. & Ogryczak, W. & Speranza, M.G., 2016. "Linear programming models based on Omega ratio for the Enhanced Index Tracking Problem," European Journal of Operational Research, Elsevier, vol. 251(3), pages 938-956.
    21. Filippi, C. & Guastaroba, G. & Speranza, M.G., 2021. "On single-source capacitated facility location with cost and fairness objectives," European Journal of Operational Research, Elsevier, vol. 289(3), pages 959-974.

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