An integrated portfolio optimisation procedure based on data envelopment analysis, artificial bee colony algorithm and genetic programming

Portfolio optimisation is an important issue in the field of investment/financial decision-making and has received considerable attention from both researchers and practitioners. However, besides portfolio optimisation, a complete investment procedure should also include the selection of profitable...

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Bibliographic Details
Published in:International journal of systems science 2014-12, Vol.45 (12), p.2645-2664
Main Author: Hsu, Chih-Ming
Format: Article
Language:English
Subjects:
artificial bee colony
data envelopment analysis
Financing
genetic programming
Investment
Markets
Operations research
Optimization
portfolio optimisation
Raw materials
Semiconductors
Swarm intelligence
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Summary:Portfolio optimisation is an important issue in the field of investment/financial decision-making and has received considerable attention from both researchers and practitioners. However, besides portfolio optimisation, a complete investment procedure should also include the selection of profitable investment targets and determine the optimal timing for buying/selling the investment targets. In this study, an integrated procedure using data envelopment analysis (DEA), artificial bee colony (ABC) and genetic programming (GP) is proposed to resolve a portfolio optimisation problem. The proposed procedure is evaluated through a case study on investing in stocks in the semiconductor sub-section of the Taiwan stock market for 4 years. The potential average 6-month return on investment of 9.31% from 1 November 2007 to 31 October 2011 indicates that the proposed procedure can be considered a feasible and effective tool for making outstanding investment plans, and thus making profits in the Taiwan stock market. Moreover, it is a strategy that can help investors to make profits even when the overall stock market suffers a loss.
ISSN:0020-7721
1464-5319
DOI:10.1080/00207721.2013.775388