Cuckoo search for portfolio optimization. (c2014)

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dc.contributor.author Medawar, Mohammad Kamal El
dc.date.accessioned 2015-02-11T12:26:27Z
dc.date.available 2015-02-11T12:26:27Z
dc.date.issued 2016-05-06
dc.date.submitted 2014-04-28
dc.identifier.uri http://hdl.handle.net/10725/1941
dc.description Includes bibliographical references (leaves 42-44). en_US
dc.description.abstract Portfolio optimization is the problem of allocating capital over different assets in order to maximize the return on the investment and/or minimize its risk, which has been a major concern for investors throughout the world. Markowitz developed the mean variance model as a part of the modern portfolio theory. When applying this theory to real-world problems, investors would force certain constraints on the solutions for a portfolio so that they meet their investment needs. Hence, the study of the portfolio optimization problem can be tackled in different ways according to the constraints to be included and the algorithms that will be applied. In this work, we design a meta-heuristic method based on Cuckoo Search (CS). Cuckoo Search is an optimization population based algorithm that imitates the reproduction strategy of cuckoos. The meta-heuristic is evaluated using different problem model parameters such as portfolio size, cardinality and lower and upper bounds. The dataset used is one provided the OR Library. The measurement of the solution quality in the results is compared with previous results and shows some improvement. For example, the CS algorithm outperformed two algorithms out of three in all datasets. In addition, it outperformed the third algorithm in 2 datasets out of 5. en_US
dc.language.iso en en_US
dc.subject Portfolio management -- Mathematical models en_US
dc.subject Mathematical optimization -- Computer programs en_US
dc.subject Investment analysis -- Mathematical models en_US
dc.subject Computer algorithms en_US
dc.subject Swarm intelligence en_US
dc.subject Dissertations, Academic en_US
dc.subject Lebanese American University -- Dissertations en_US
dc.title Cuckoo search for portfolio optimization. (c2014) en_US
dc.type Thesis en_US
dc.term.submitted Spring en_US
dc.author.degree MS in Computer Science en_US
dc.author.school SAS en_US
dc.author.idnumber 200703157 en_US
dc.author.commembers Dr. Sanaa Sharafeddine
dc.author.commembers Dr. Azzam Mourad
dc.author.woa OA en_US
dc.description.physdesc 1 hard copy: x, 44 leaves; ill.; 30 cm. available at RNL. en_US
dc.author.division Computer Science en_US
dc.author.advisor Dr. Nashat Mansour
dc.keywords Cuckoo Search en_US
dc.keywords Portfolio Optimization en_US
dc.keywords Markowitz en_US
dc.keywords Mean en_US
dc.keywords Variance en_US
dc.identifier.doi https://doi.org/10.26756/th.2014.22 en_US
dc.publisher.institution Lebanese American University en_US

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