Implementation of agglomerative clustering and modified artificial bee colony algorithm on stock portfolio optimization with possibilistic constraints

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Abstract

Portfolio optimization problem is a fundamental matter in the financial environment, where the investors form a satisfactory portfolio by obtaining optimal return and minimal risk. In this paper, we discuss the portfolio optimization problem with real-world constraints such as transaction costs, cardinality, and quantity under the assumption that the returns of risky stocks are fuzzy numbers. Thus, a mixed integer model nonlinear programming problem is discussed. At first, stock data is diversified based on their financial ratio scores by using Agglomerative Clustering to produce a homogeneous cluster. Next, the proportion of each stock in the stock portfolio is determined using a modified artificial bee colony algorithm, where in the algorithm there is a process of chaotic initialization approach. Finally, the obtained return will be compared to both the S&P 500 index return (12.34 %) and sharpe ratio (2.7). The result forms the performance of Modified Artificial Bee Colony Algorithm with Agglomerative Clustering in portfolio optimization, evaluated based on some actual dataset, showing that the higher level of return is 29.96 % and sharpe ratio is 17.562.

Original languageEnglish
Title of host publicationProceedings of the 4th International Symposium on Current Progress in Mathematics and Sciences, ISCPMS 2018
EditorsTerry Mart, Djoko Triyono, Ivandini T. Anggraningrum
PublisherAmerican Institute of Physics Inc.
ISBN (Electronic)9780735419155
DOIs
Publication statusPublished - 4 Nov 2019
Event4th International Symposium on Current Progress in Mathematics and Sciences 2018, ISCPMS 2018 - Depok, Indonesia
Duration: 30 Oct 201831 Oct 2018

Publication series

NameAIP Conference Proceedings
Volume2168
ISSN (Print)0094-243X
ISSN (Electronic)1551-7616

Conference

Conference4th International Symposium on Current Progress in Mathematics and Sciences 2018, ISCPMS 2018
CountryIndonesia
CityDepok
Period30/10/1831/10/18

Keywords

  • Agglomerative clustering
  • fuzzy numbers
  • portfolio optimizaton

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