A similarity measure for the cardinality constrained frontier in the mean–variance optimization modelFootnote

Please note this paper has been re-typeset by Taylor & Francis from the manuscript originally provided to the previous publisher.

References

• Ahn, J. J., Byun, H. W., Oh, K. J., & Kim, T. Y. (2012). Using ridge regression with genetic algorithm to enhance real estate appraisal forecasting. Expert Systems with Applications, 39(9), 8369–8379.
   Web of Science ®Google Scholar
• Anagnostopoulos, K. P., & Mamanis, G. (2011). The mean–variance cardinality constrained portfolio optimization problem: An experimental evaluation of five multiobjective evolutionary algorithms. Expert Systems with Applications, 38(11), 14208–14217.
   Web of Science ®Google Scholar
• Aouni, B., Colapinto, C., & La Torre, D. (2013). A cardinality constrained stochastic goal programming model with satisfaction functions for venture capital investment decision making. Annals of Operations Research, 205(1), 77–88.
   Web of Science ®Google Scholar
• Barak, S., Abessi, M., & Modarres, M. (2013). Fuzzy turnover rate chance constraints portfolio model. European Journal of Operational Research, 228(1), 141–147.
   Web of Science ®Google Scholar
• Beasley, J. E. (1990). OR-Library: Distributing test problems by electronic mail. Journal of the Operational Research Society, 41(11), 1069–1072.
   Web of Science ®Google Scholar
• Bertsimas, D., & Shioda, R. (2009). Algorithm for cardinality-constrained quadratic optimization. Computational Optimization and Applications, 43(1), 1–22.
   Web of Science ®Google Scholar
• Bienstock, D. (1995). Computational study of a family of mixed integer quadratic programming problems. Mathematical Programming, 74(2), 121–140.
   Web of Science ®Google Scholar
• Canakgoz, N. A., & Beasley, J. E. (2009). Mixed-integer programming approaches for index tracking and enhanced indexation. European Journal of Operational Research, 196(1), 384–399.
   Web of Science ®Google Scholar
• 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.
   Web of Science ®Google Scholar
• 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.
   Web of Science ®Google Scholar
• 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.
   Web of Science ®Google Scholar
• Chiam, S. C., Tan, K. C., & Al Mamun, A. (2013). Dynamic index tracking via multi-objective evolutionary algorithm. Applied Soft Computing, 13(7), 3392–3408.
   Web of Science ®Google Scholar
• Di Tollo, G., & Rolli, A. (2008). Metaheuristics for the portfolio selection problem. International Journal of Operations Research, 5(1), 13–35.
   Google Scholar
• García, F., Guijarro, F., & Moya, I. (2011). The curvature of the tracking frontier: A new criterion for the partial index tracking problem. Mathematical and Computer Modelling, 54(7), 1781–1784.
   Google Scholar
• Holland, J. H. (1975). Adaptation in natural and artificial systems: An introductory analysis with applications to biology, control and artificial intelligence. Cambridge: The MIT Press.
   Google Scholar
• Krink, T., Mittnik, S., & Paterlini, S. (2009). Differential evolution and combinatorial search for constrained index-tracking. Annals of Operations Research, 172(1), 153–176.
   Web of Science ®Google Scholar
• Lajili-Jarjir, S., & Rakotondratsimba, Y. (2006). The number of securities giving the maximum return in the presence of transaction costs. Quality and Quantity, 42(5), 613–644.
   Google Scholar
• Li, D., Sun, X., & Wang, J. (2006). Optimal lot solution to cardinality constrained mean–variance formulation for portfolio selection. Mathematical Finance, 16(1), 83–101.
   Web of Science ®Google Scholar
• 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.
   Web of Science ®Google Scholar
• Lwin, K., & Qu, R. (2013). A hybrid algorithm for constrained portfolio selection problems. Applied Intelligence, 39(2), 251–266.
   Web of Science ®Google Scholar
• Maringer, D., & Kellerer, H. (2003). Optimization of cardinality constrained portfolios with a hybrid local search algorithm. OR Spectrum, 25(4), 481–495.
   Web of Science ®Google Scholar
• Markowitz, H. (1952). Portfolio selection. Journal of Finance, 7(1), 77–91.
   Web of Science ®Google Scholar
• Meade, N., & Salkin, G. (1990). Developing and maintaining an equity index fund. The Journal of the Operational Research Society, 41(7), 599–607.
   Web of Science ®Google Scholar
• Merton, R. C. (1972). An analytic derivation of the efficient portfolio frontier. The Journal of Financial and Quantitative Analysis, 7(4), 1851–1872.
   Web of Science ®Google Scholar
• Metaxiotis, K., & Liagkouras, K. (2012). Multiobjective evolutionary algorithms for portfolio management: A comprehensive literature review. Expert Systems with Applications, 39(14), 11685–11698.
   Web of Science ®Google Scholar
• Ruiz-Torrubiano, R., & Suárez, A. (2009). A hybrid optimization approach to index tracking. Annals of Operations Research, 166(1), 57–71.
   Web of Science ®Google Scholar
• Sant’Anna, L. R., Filomena, T. P., Guedes, P. C., & Borenstein, D. (2016). Index tracking with controlled number of assets using a hybrid heuristic combining genetic algorithm and non-linear programming. Annals of Operations Research. Advance online publication 3 February. doi:10.1007/s10479-016-2111-x
   Google Scholar
• Shaw, D., Liu, S., & Kopman, L. (2008). Lagrangian relaxation procedure for cardinality-constrained portfolio optimization. Optimisation Methods & Software, 23(3), 411–420.
   Web of Science ®Google Scholar
• Woodside-Oriakhi, M., Lucas, C., & Beasley, J. (2011). Heuristic algorithms for the cardinality constrained efficient frontier. European Journal of Operational Research, 213(3), 538–550.
   Web of Science ®Google Scholar
• Zitzler, E., & Thiele, L. (1998). Multiobjective optimization using evolutionary algorithms – A comparative case study. In Proceedings of PPSN-V, Fifth International Conference on Parallel Problem Solving from Nature (pp. 292–301). Berlin: Springer.
   Google Scholar