Implementation of improved quick artificial Bee Colony Algorithm on portfolio optimization problems with constraints

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Citations (Scopus)

Abstract

In investing, every investor wants an optimal portfolio that generates a high return with minimal risk. There are many portfolio optimization models, among which is the Mean-Variance (MV) model. This model minimizes the portfolio variances that represents the risk in investment. The Artificial Bee Colony (ABC) is a heuristic method that can be used to solve the portfolio optimization problems. This method is inspired by the movement of honey bee colonies when searching for food. In this study, both the Cardinality-constrained mean-variance (CCMV) model and Improved Quick Artificial Bee Colony (iqABC) method were used. In this case, the CCMV model is a modification of the MV model which adds the cardinality constraint, quantity constraints, and the investor risk tolerance parameter. Meanwhile, the iqABC method is developed from the ABC method. The implementation shows that the choice of parameters in CCMV model must be chosen carefully, since the choice may help the investors compose the portfolio that suits their risk tolerance with diversification in mind. The implementation also shows the iqABC method on CCMV model generates a portfolio with better returns and Sharpe ratio values compared to those of mABC methods and the market.

Original languageEnglish
Title of host publicationProceedings of the 5th International Symposium on Current Progress in Mathematics and Sciences, ISCPMS 2019
EditorsTerry Mart, Djoko Triyono, Tribidasari Anggraningrum Ivandini
PublisherAmerican Institute of Physics Inc.
ISBN (Electronic)9780735420014
DOIs
Publication statusPublished - 1 Jun 2020
Event5th International Symposium on Current Progress in Mathematics and Sciences, ISCPMS 2019 - Depok, Indonesia
Duration: 9 Jul 201910 Jul 2019

Publication series

NameAIP Conference Proceedings
Volume2242
ISSN (Print)0094-243X
ISSN (Electronic)1551-7616

Conference

Conference5th International Symposium on Current Progress in Mathematics and Sciences, ISCPMS 2019
Country/TerritoryIndonesia
CityDepok
Period9/07/1910/07/19

Keywords

  • cardinality-constrained mean-variance model
  • improved quick artificial bee colony method
  • Portfolio

Fingerprint

Dive into the research topics of 'Implementation of improved quick artificial Bee Colony Algorithm on portfolio optimization problems with constraints'. Together they form a unique fingerprint.

Cite this