156
Views
3
CrossRef citations to date
0
Altmetric
Original Articles

A surrogate similarity measure for the mean-variance frontier optimisation problem under bound and cardinality constraints

ORCID Icon &
Pages 564-579 | Received 18 Feb 2019, Accepted 09 Aug 2019, Published online: 18 Dec 2019

References

  • Beasley, J. E. (1990). OR-Library: Distributing test problems by electronic mail. Journal of the Operational Research Society, 41(11), 1069–1072. doi:10.1057/jors.1990.166
  • Bruni, R., Cesarone, F., Scozzari, A., & Tardella, F. (2015). A linear risk-return model for enhanced indexation in portfolio optimization. OR Spectrum, 37(3), 735–759. doi:10.1007/s00291-014-0383-6
  • Bruni, R., Cesarone, F., Scozzari, A., & Tardella, F. (2016). Real-world datasets for portfolio selection and solutions of some stochastic dominance portfolio models. Data in Brief, 8, 858–862. doi:10.1016/j.dib.2016.06.031
  • Cesarone, F., Scozzari, A., & Tardella, F. (2013). A new method for mean-variance portfolio optimization with cardinality constraints. Annals of Operations Research, 205(1), 213–234. doi:10.1007/s10479-012-1165-7
  • Chang, T. J., Meade, N., Beasley, J. E., & Sharaiha, Y. M. (2000). Heuristics for cardinality constrained portfolio optimisation. Computers & Operations Research, 27(13), 1271–1302. doi:10.1016/S0305-0548(99)00074-X
  • Chang, T. J., Yang, S. C., & Chang, K. J. (2009). Portfolio optimization problems in different risk measures using genetic algorithm. Expert Systems with Applications, 36(7), 10529–10537. doi:10.1016/j.eswa.2009.02.062
  • Cura, T. (2009). Particle swarm optimization approach to portfolio optimization. Nonlinear Analysis: Real World Applications, 10(4), 2396–2406. doi:10.1016/j.nonrwa.2008.04.023
  • Deng, G. F., Lin, W. T., & Lo, C. C. (2012). Markowitz-based portfolio selection with cardinality constraints using improved particle swarm optimization. Expert Systems with Applications, 39(4), 4558–4566. doi:10.1016/j.eswa.2011.09.129
  • Guijarro, F. (2018). A similarity measure for the cardinality constrained frontier in the mean-variance optimization model. Journal of the Operational Research Society, 69(6), 928–945. doi:10.1057/s41274-017-0276-6
  • Kalayci, C. B., Ertenlice, O., Akyer, H., & Aygoren, H. (2017). An artificial bee colony algorithm with feasibility enforcement and infeasibility toleration procedures for cardinality constrained portfolio optimization. Expert Systems with Applications, 85, 61–75. doi:10.1016/j.eswa.2017.05.018
  • Li, D., & Ng, W.-L. (2000). Optimal dynamic portfolio selection: Multiperiod mean-variance formulation. Mathematical Finance, 10(3), 387–406. doi:10.1111/1467-9965.00100
  • Liagkouras, K., & Metaxiotis, K. (2014). A new probe guided mutation operator and its application for solving the cardinality constrained portfolio optimization problem. Expert Systems with Applications, 41(14), 6274–6290. doi:10.1016/j.eswa.2014.03.051
  • Lwin, K., & Qu, R. (2013). A hybrid algorithm for constrained portfolio selection problems. Applied Intelligence, 39(2), 251–266. doi:10.1007/s10489-012-0411-7
  • Markowitz, H. (1952). Portfolio selection. The Journal of Finance, 7(1), 77–91. doi:10.1111/j.1540-6261.1952.tb01525.x
  • Meghwani, S. S., & Thakur, M. (2017). Multi-criteria algorithms for portfolio optimization under practical constraints. Swarm and Evolutionary Computation, 37, 104–125. doi:10.1016/j.swevo.2017.06.005
  • Moscato, P., & Cotta, C. (2003). A gentle introduction to memetic algorithms. In F. Glover & G. Kochenberger (Eds.), Handbook of metaheuristics (pp. 105–144). Berlin, Germany: Springer.
  • Peterson, B., & Carl, P. (2018). Performance analytics: Econometric tools for performance and risk analysis. Retrieved from https://CRAN.R-project.org/package=PerformanceAnalytics
  • Ruiz-Torrubiano, R., & Suárez, A. (2009). A hybrid optimization approach to index tracking. Annals of Operations Research, 166(1), 57–71. doi:10.1007/s10479-008-0404-4
  • Ruiz-Torrubiano, R., & Suárez, A. (2015). A memetic algorithm for cardinality-constrained portfolio optimization with transaction costs. Applied Soft Computing, 36, 125–142. doi:10.1016/j.asoc.2015.06.053
  • Sadjadi, S. J., Gharakhani, M., & Safari, E. (2012). Robust optimization framework for cardinality constrained portfolio problem. Applied Soft Computing, 12(1), 91–99. doi:10.1016/j.asoc.2011.09.006
  • Salehpoor, I. B., & Molla-Alizadeh-Zavardehi, S. (2019). A constrained portfolio selection model at considering risk-adjusted measure by using hybrid meta-heuristic algorithms. Applied Soft Computing, 75, 233–253. doi:10.1016/j.asoc.2018.11.011
  • Shaw, D. X., Liu, S., & Kopman, L. (2008). Lagrangian relaxation procedure for cardinality-constrained portfolio optimization. Optimization Methods and Software, 23(3), 411–420. doi:10.1080/10556780701722542
  • Soleimani, H., Golmakani, H. R., & Salimi, M. H. (2009). Markowitz-based portfolio selection with minimum transaction lots, cardinality constraints and regarding sector capitalization using genetic algorithm. Expert Systems with Applications, 36(3), 5058–5063. doi:10.1016/j.eswa.2008.06.007
  • Woodside-Oriakhi, M., Lucas, C., & Beasley, J. E. (2011). Heuristic algorithms for the cardinality constrained efficient frontier. European Journal of Operational Research, 213(3), 538–550. doi:10.1016/j.ejor.2011.03.030

Reprints and Corporate Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

To request a reprint or corporate permissions for this article, please click on the relevant link below:

Academic Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

Obtain permissions instantly via Rightslink by clicking on the button below:

If you are unable to obtain permissions via Rightslink, please complete and submit this Permissions form. For more information, please visit our Permissions help page.