International Journal of Computational Intelligence Systems

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Volume 11, Issue 1, 2018, Pages 1016 - 1029

Resolving a portfolio optimization problem with investment timing through using the analytic hierarchy process, support vector regression and a genetic algorithm

Authors
Chih-Ming Hsu*cmhsu@must.edu.tw
Department of Business Administration, Minghsin University of Science and Technology, No. 1 Hsin-Hsing Rd., Hsin-Fong, Hsinchu, Taiwan
Received 22 January 2018, Accepted 11 May 2018, Available Online 28 May 2018.
DOI
10.2991/ijcis.11.1.77How to use a DOI?
Keywords
Stock investment; Portfolio optimization; Analytic hierarchy process; Support vector regression; Genetic algorithm
Abstract

In the field of financial investment, investing in stocks is relatively easy compared to other investment commodities, since making a profit through buying a stock at a low price and selling it at a higher price is intuitive. However, it is really challenging work for an investor to choose stocks which might be profitable, to determine the capital allocations for these selected stocks or even to time the transactions for stocks. In this study, the analytic hierarchy process (AHP), support vector regression (SVR), and genetic algorithm (GA) are employed to design a three-stage portfolio optimization approach for sequentially solving the portfolio selection, portfolio optimization, and transaction timing. Stocks in the semiconductor and iron and steel subsectors in Taiwan are used to illustrate the procedures for applying the present approach. Based on the investment results from 26 May 2017 to 25 Aug. 2017, the annualized returns on investment are 15.36% and 6.15% for the stock markets of the semiconductor and iron and steel sub-sections, respectively. Both returns are superior to the one-year certificate of deposit of about 1% in Taiwan. Hence, we are confident that the proposed approach can fit the real-world stock market, and thus serve as a valuable, functional tool for an investor.

Copyright
© 2018, the Authors. Published by Atlantis Press.
Open Access
This is an open access article under the CC BY-NC license (http://creativecommons.org/licences/by-nc/4.0/).

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Journal
International Journal of Computational Intelligence Systems
Volume-Issue
11 - 1
Pages
1016 - 1029
Publication Date
2018/05/28
ISSN (Online)
1875-6883
ISSN (Print)
1875-6891
DOI
10.2991/ijcis.11.1.77How to use a DOI?
Copyright
© 2018, the Authors. Published by Atlantis Press.
Open Access
This is an open access article under the CC BY-NC license (http://creativecommons.org/licences/by-nc/4.0/).

Cite this article

risenwbib
TY  - JOUR
AU  - Chih-Ming Hsu*
PY  - 2018
DA  - 2018/05/28
TI  - Resolving a portfolio optimization problem with investment timing through using the analytic hierarchy process, support vector regression and a genetic algorithm
JO  - International Journal of Computational Intelligence Systems
SP  - 1016
EP  - 1029
VL  - 11
IS  - 1
SN  - 1875-6883
UR  - https://doi.org/10.2991/ijcis.11.1.77
DO  - 10.2991/ijcis.11.1.77
ID  - Hsu*2018
ER  -