Implementation of density-based spatial clustering of application with noise and genetic algorithm in portfolio optimization with constraint

R. S. Dinandra, G. F. Hertono, B. D. Handari

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

1 Citation (Scopus)

Abstract

Every investor is hoping to get a high rate of return for their portfolio with as little risk as possible, so investors try to balance the performance and risk of the portfolio through diversification. Diversification is a technique to improve the performance of the portfolio by minimizing the risk of the portfolio. The motivation of this research is to investigate the portfolio selection strategies through clustering method and application of the genetic algorithm. Clustering is used to diversify the portfolio by forming a homogenous cluster with respect to their financial ratios. Seven financial ratio characteristics that used are Earning Per Share (EPS), Price Earnings Ratio (PER), Price / Earnings Growth (PEG), Return of Equity (ROE), Debt Equity Ratio (DER), Current Ratio (CR) and Profit Margin (PM). Density-based Spatial Clustering of Application with Noise (DBSCAN) used as clustering method, then Genetic Algorithm (GA) used for portfolio selection. GA automatically select the optimum risk and return portfolio based on the clustered stocks by deciding which assets and their respective weights included in the portfolio. The GA constructed based on Mean Variance Cardinality Constrained Portfolio Optimization (MVCCPO) model and called a Constrained Genetic Algorithm. The method successfully gives a higher level of return (41.05 %) and Sharpe ratio (32.67) compared to the S&P 500 index in the same period of time (12.34 % and 2.7 respectively).

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

  • Density-based spatial clustering
  • diversification
  • investing

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