Portfolio Optimization Using the Bat Algorithm

Hamza Kamili; M. E. Riffi

doi:10.15866/irecos.v11i3.8154

Portfolio Optimization Using the Bat Algorithm

Hamza Kamili^(1*), M. E. Riffi⁽²⁾

^(*) Corresponding author

Authors' affiliations

DOI: https://doi.org/10.15866/irecos.v11i3.8154

Abstract

The bat algorithm is a meta-heuristic algorithm inspired by the bats behaviour characterized by using the echolocation process to localize their objective. In this work applied the bat algorithm has been used in order to solve the portfolio selection problem. This method has been adapted to the cardinality constrained efficient frontier model CCEF using four indexes Hang Seng in Hong Kong, DAX 100 in Germany FTSE 100 in USA and NIKKEI in Japan and the obtained results were compared to those of the unconstrained efficient frontier model (UEF). The bat method illustrates an optimal approximation between the constrained and the unconstrained models.
Copyright © 2016 Praise Worthy Prize - All rights reserved.

Keywords

Bat Algorithm; Cardinality Constrained Efficient Frontier Model; Markowitz Model; Meta-Heuristic

Full Text:

PDF

References

M. S. Lobo, M. Fazel, S. Boyd, Portfolio Optimization With linear and fixed transaction costs, Annals of Operations Research, Vol. 152, No.1, pp.341-365, December 2006.
http://dx.doi.org/10.1007/s10479-006-0145-1

V. Demiguel, L. Garlappi, F. J. Nogales, R. Uppal, A Generalized Approach to Portfolio Optimization: Improving Performance by Constraining Portfolio Norms, Management Science journal, vol. 55, pp. 789-812, 2007
http://dx.doi.org/10.1287/mnsc.1080.0986

V. Tola, F. Lillo, M. Gallegati, R. N. Mantegna, Cluster Analysis For Portfolio Optimization, journal of Economic Dynamics and control, vol. 32, pp. 235-258, January 2008
http://dx.doi.org/10.1016/j.jedc.2007.01.034

H.Markowitz , portfolio Selection, The journal of finance, Vol.7, No 1,pp.77-91.
http://dx.doi.org/10.1111/j.1540-6261.1952.tb01525.x

T. J. Chang, N. Meade, J. E. Beasley, Y. M. Sharaiha, Heuristics for Cardinality Constrained Portfolio Optimization, Computers& operations Research ,Vol.27,pp.1271-1302, 2000.
http://dx.doi.org/10.1016/s0305-0548(99)00074-x

Xin-She Yang, A New Metaheuristics Bat-Inspired Algorithm, Nature Inspired Cooperative Strategies for Optimization (NICSO 2010) Studies in Computational Intelligence ,Vol .284, pp.65 -74, 2010.
http://dx.doi.org/10.1007/978-3-642-12538-6_6

J. W. Zhang, G. G. Wang, Image Matching Using A Bat Algorithm With Mutation, Applied mechanics and materials, Vol. 203, pp. 88-93, oct 2012.
http://dx.doi.org/10.4028/www.scientific.net/amm.203.88

B. Ramesh,V.C.J Mohan,V.C.V.Reddy, Application Of Bat Algorithm For Combined Economic Load And Emission Dispatch, International Journal Of Electrical And Electronics Engineering & Telecommucations , Vol.2, No.1, pp. 2319-2518, January 2013.

J.H.Lin, C.W.Chou, C.H,Yang, H.L.Tsai, A Chaotic Levy Flight Bat Algorithm for Parameter Estimation in nonlinear Dynamic Biologiacal Systems, journal of computer and Information Technology , Vol.2, No.2, pp.2161-7112.

Y .Crama, M. Schyns, Simulated Annealing For Complex Portfolio Selection Problems, European Journal of Operational Research,Vol.150, pp. 546–57, 2003.
http://dx.doi.org/10.1016/s0377-2217(02)00784-1

W. G. Zhang, W .Chen and Y.L. Wang, The Adaptive Genetic Algorithms For Portfolio Selection Problem, International Journal of Computer Science and Network Security, Vol.6, pp 196-200, 2006.

T .Shankar, S .Shanmugavel, A . Karthikeyan, Hybrid Approach for Energy optimization in Wireless Sensor Nerworks Using PSO, Journal of International Review on Computers and Software , vol., n.3, pp.1454 -1459, 2013.

T. Cura, Particle Swarm Optimization Approach To Portfolio Optimization, Expert Systems With Applications, Vol.10, 200, pp. 2396-2406, 2009.
http://dx.doi.org/10.1016/j.nonrwa.2008.04.023

K.F .Haqiqi, T. Kazemi, Ant Colony Optimization Approach To Portfolio Optimization, International Conference on Economics, Business and Marketing Management, Vol.29, pp. 292-296, 2012.
http://dx.doi.org/10.7763/ijtef.2012.v3.189

A. Fernandez , S. Gomez, Portfolio Selection Using Neural Networks, Computers & Operations Research ,Vol.34, pp. 1177-1191, 2007
http://dx.doi.org/10.1016/j.cor.2005.06.017

A. D’Ariano, D. Pacciarelli, M. Pranzo, A Branch and Bound Algorithm for Sheduling Trains in a Railway Network, European Journal of Operational Research , vol. 183, pp. 643-657, Decembre 2007.
http://dx.doi.org/10.1016/j.ejor.2006.10.034

S. J. Kim, K. Koh, M. Lustig, S. Boy, D. Gorinevsky, An Interior-Point Method for Large Scale | 1- Regularise Least squares, Journal of selected Topics in Signal Processing, vol.1, No. 4, pp. 606-617, December 2007.
http://dx.doi.org/10.1109/jstsp.2007.910971

Santiprapan, P., Areerak, K., Areerak, K., The Enhanced – DQF Algorithm and Optimal Controller Design for Shunt Active Power Filter, (2015) International Review of Electrical Engineering (IREE), 10(5), pp. 578-590.
http://dx.doi.org/10.15866/iree.v10i5.7364

Manh, L., Grimaccia, F., Mussetta, M., Zich, R., A Soft Computing Hybridization Technique for Antenna Optimization, (2015) International Journal on Communications Antenna and Propagation (IRECAP), 5(1), pp. 16-20.
http://dx.doi.org/10.15866/irecap.v5i1.4899

Refbacks

There are currently no refbacks.

Username
Password
Remember me