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Index tracking optimization with cardinality constraint: a performance comparison of genetic algorithms and tabu search heuristics

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Index tracking optimization with cardinality constraint: a performance comparison of genetic algorithms and tabu search heuristics

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dc.contributor.author García García, Fernando es_ES
dc.contributor.author Guijarro, Francisco es_ES
dc.contributor.author Oliver-Muncharaz, Javier es_ES
dc.date.accessioned 2019-06-07T20:02:29Z
dc.date.available 2019-06-07T20:02:29Z
dc.date.issued 2018 es_ES
dc.identifier.issn 0941-0643 es_ES
dc.identifier.uri http://hdl.handle.net/10251/121737
dc.description.abstract [EN] The aim of this study was to compare the performance of the well-known genetic algorithms and tabu search heuristics with the financial problem of the partial tracking of a stock market index. Although the weights of each stock in a tracking portfolio can be efficiently determined by means of quadratic programming, identifying the appropriate stocks to include in the portfolio is an NP-hard problem which can only be addressed by heuristics. Seven real-world indexes were used to compare the above techniques, and results were obtained for different tracking portfolio cardinalities. The results show that tabu search performs more efficiently with both real and artificial indexes. In general, the tracking portfolios obtained performed well in both in-sample and out-of-sample periods, so that these heuristics can be considered as appropriate solutions to the problem of tracking an index by means of a small subset of stocks. es_ES
dc.language Inglés es_ES
dc.publisher Springer-Verlag es_ES
dc.relation.ispartof Neural Computing and Applications es_ES
dc.rights Reserva de todos los derechos es_ES
dc.subject Index tracking es_ES
dc.subject Heuristics es_ES
dc.subject S&P 500 es_ES
dc.subject Artificial index es_ES
dc.subject.classification ECONOMIA FINANCIERA Y CONTABILIDAD es_ES
dc.title Index tracking optimization with cardinality constraint: a performance comparison of genetic algorithms and tabu search heuristics es_ES
dc.type Artículo es_ES
dc.identifier.doi 10.1007/s00521-017-2882-2 es_ES
dc.rights.accessRights Abierto es_ES
dc.date.embargoEndDate 2019-10-01 es_ES
dc.contributor.affiliation Universitat Politècnica de València. Departamento de Economía y Ciencias Sociales - Departament d'Economia i Ciències Socials es_ES
dc.description.bibliographicCitation García García, F.; Guijarro, F.; Oliver-Muncharaz, J. (2018). Index tracking optimization with cardinality constraint: a performance comparison of genetic algorithms and tabu search heuristics. Neural Computing and Applications. 30(8):2625-2641. https://doi.org/10.1007/s00521-017-2882-2 es_ES
dc.description.accrualMethod S es_ES
dc.relation.publisherversion http://doi.org/10.1007/s00521-017-2882-2 es_ES
dc.description.upvformatpinicio 2625 es_ES
dc.description.upvformatpfin 2641 es_ES
dc.type.version info:eu-repo/semantics/publishedVersion es_ES
dc.description.volume 30 es_ES
dc.description.issue 8 es_ES
dc.relation.pasarela S\367719 es_ES
dc.description.references Aguilar-Rivera R, Valenzuela-Rendón M, Rodríguez-Ortiz JJ (2015) Genetic algorithms and Darwinian approaches in financial applications: a survey. Expert Syst Appl 42:7684–7697 es_ES
dc.description.references Andriosopoulos K, Doumpos M, Papapostolou NC, Pouliasis PK (2013) Portfolio optimization and index tracking for the shipping stock and freight markets using evolutionary algorithms. Transp Res Part E Logist Transp Rev 52:16–34 es_ES
dc.description.references Aouni B, Colapinto C, La Torre D (2013) A cardinality constrained stochastic goal programming model with satisfaction functions for venture capital investment decision making. Ann Oper Res 205:77–88 es_ES
dc.description.references Barak S, Dahooie JH, Tichý T (2015) Wrapper ANFIS-ICA method to do stock market timing and feature selection on the basis of Japanese candlestick. Expert Syst Appl 42:9221–9235 es_ES
dc.description.references Beasley JE (1990) OR-Library: distributing test problems by electronic mail. J Oper Res Soc 41:1069–1072 es_ES
dc.description.references Beasley JE, Meade N, Chang TJ (2003) An evolutionary heuristic for the index tracking problem. Eur J Oper Res 148:621–643 es_ES
dc.description.references Berutich JM, López F, Luna F, Quintana D (2016) Robust technical trading strategies using GP for algorithmic portfolio selection. Expert Syst Appl 46:307–315 es_ES
dc.description.references Canakgoz NA, Beasley JE (2008) Mixed-integer programming approaches for index tracking and enhanced indexation. Eur J Oper Res 196:384–399 es_ES
dc.description.references Cesarone F, Scozzari A, Tardella F (2013) A new method for mean-variance portfolio optimization with cardinality constraints. Ann Oper Res 205:213–234 es_ES
dc.description.references Chang TJ, Meade N, Beasley JE, Sharaiha YM (2000) Heuristics for cardinality constrained portfolio optimisation. Comput Oper Res 27:1271–1302 es_ES
dc.description.references Chavez-Bedoya L, Birge JR (2014) Index tracking and enhanced indexation using a parametric approach. J Econ Financ Adm Sci 19:19–44 es_ES
dc.description.references Chen C, Kwon RH (2012) Robust portfolio selection for index tracking. Comput Oper Res 39:829–837 es_ES
dc.description.references Chiam SC, Tan KC, Al Mamun A (2013) Dynamic index tracking via multi-objective evolutionary algorithm. Appl Soft Comput J 13:3392–3408 es_ES
dc.description.references Connor G, Leland H (1995) Cash management for index tracking. Financ Anal J 51:75–80 es_ES
dc.description.references Corielli F, Marcellino M (2006) Factor based index tracking. J Bank Financ 30:2215–2233 es_ES
dc.description.references Dunis CL, Rosillo R, de la Fuente D, Pino R (2013) Forecasting IBEX-35 moves using support vector machines. Neural Comput Appl 23:229–236 es_ES
dc.description.references Fama EF (1970) efficient capital markets: a review of theory and empirical work. J Financ 25:383–417 es_ES
dc.description.references Filippi C, Guastaroba G, Speranza MG (2016) A heuristic framework for the bi-objective enhanced index tracking problem. Omega 65:122–137 es_ES
dc.description.references Franks EC (1992) Targeting excess-of-benchmark returns. J Portf Manag 18:6–12 es_ES
dc.description.references Frino A, Gallagher DR, Oetomo TN (2005) The index tracking strategies of passive and enhanced index equity funds. Aust J Manag 30:23–55 es_ES
dc.description.references García F, Guijarro F, Moya I (2011) The curvature of the tracking frontier: a new criterion for the partial index tracking problem. Math Comput Model 54:1781–1784 es_ES
dc.description.references Glover F (1986) Future paths for integer programming an links to artificial intelligence. Comput Oper Res 13:533–549 es_ES
dc.description.references Guastaroba G, Speranza MG (2012) Kernel search: an application to the index tracking problem. Eur J Oper Res 217:54–68 es_ES
dc.description.references Holland JH (1975) Adaptation in natural and artificial systems. An introductory analysis with applications to biology, control and artificial intelligence. University of Michigan Press, Ann Arbor es_ES
dc.description.references Hsu C (2013) A hybrid procedure with feature selection for resolving stock/futures price forecasting problems. Neural Comput Appl 22:651–671 es_ES
dc.description.references Li Q, Sun L, Bao L (2011) Enhanced index tracking based on multi-objective immune algorithm. Expert Syst Appl 38:6101–6106 es_ES
dc.description.references Li X, Xie H, Wang R, Cai Y, Cao J, Wang F, Min H, Deng X (2014) Empirical analysis: stock market prediction via extreme learning machine. Neural Comput Appl 27:67–78 es_ES
dc.description.references Lindemann A, Dunis CL, Lisboa P (2005) Level estimation, classification and probability distribution architectures for trading the EUR/USD exchange rate. Neural Comput Appl 14:256–271 es_ES
dc.description.references Lobo MS, Fazel M, Boyd S (2007) Portfolio optimization with linear and fixed transaction costs. Ann Oper Res 152:341–365 es_ES
dc.description.references Lwin K, Qu R (2013) A hybrid algorithm for constrained portfolio selection problems. Appl Intell 39:251–266 es_ES
dc.description.references Maringer D, Kellerer H (2003) Optimization of cardinality constrained portfolios with a hybrid local search algorithm. OR Spectr 25:481–495 es_ES
dc.description.references Markowitz H (1952) Portfolio selection. J Financ 7:77–91 es_ES
dc.description.references Mezali H, Beasley JE (2014) Index tracking with fixed and variable transaction costs. Optim Lett 8:61–80 es_ES
dc.description.references Ni H, Wang Y (2013) Stock index tracking by Pareto efficient genetic algorithm. Appl Soft Comput J 13:4519–4535 es_ES
dc.description.references Roll R (1992) A mean/variance analysis of tracking error. J Portf Manag 18:13–22 es_ES
dc.description.references Ruiz-Torrubiano R, Suárez A (2009) A hybrid optimization approach to index tracking. Ann Oper Res 166:57–71 es_ES
dc.description.references Sant’Anna LR, Filomena RP, Guedes PC, Borenstein D (2016) Index tracking with controlled number of assets using a hybrid heuristic combining genetic algorithm and non-linear programming. Ann Oper Res. doi: 10.1007/s10479-016-2111-x es_ES
dc.description.references Shoven JB, Sialm C (2000) The Dow Jones industrial average: the impact of fixing its flaws. J Wealth Manag 3:9–18 es_ES
dc.description.references Streichert F, Ulmer H, Zell A (2004) Evolutionary algorithms and the cardinality constrained portfolio optimization problem. In: Proceedings of the operations research 2003. Springer, Berlin, pp 253–260 es_ES
dc.description.references Thenmozhi M, Sarath Chand G (2016) Forecasting stock returns based on information transmission across global markets using support vector machines. Neural Comput Appl 27:805–824 es_ES
dc.description.references Wang M, Xu C, Xu F, Xue H (2012) A mixed 0–1 LP for index tracking problem with CVaR risk constraints. Ann Oper Res 196:591–609 es_ES
dc.description.references Woodside-Oriakhi M, Lucas C, Beasley JE (2011) Heuristic algorithms for the cardinality constrained efficient frontier. Eur J Oper Res 213:538–550 es_ES


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