Selecting and Weighting Mechanisms in Stock Portfolio Design Based on Clustering Algorithm and Price Movement Analysis

The fundamental stages in designing a stock portfolio are each stock’s selection and capital weighting. Selection and weighting must be conducted through diversification and price movement analysis to maximize profits and minimize losses. The problem is how the technical implementations of both are...

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Main Authors: Titi Purwandari, Riaman, Yuyun Hidayat, Sukono, Riza Andrian Ibrahim, Rizki Apriva Hidayana
Format: Article
Language:English
Published: MDPI AG 2023-10-01
Series:Mathematics
Subjects:
Online Access:https://www.mdpi.com/2227-7390/11/19/4151
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author Titi Purwandari
Riaman
Yuyun Hidayat
Sukono
Riza Andrian Ibrahim
Rizki Apriva Hidayana
author_facet Titi Purwandari
Riaman
Yuyun Hidayat
Sukono
Riza Andrian Ibrahim
Rizki Apriva Hidayana
author_sort Titi Purwandari
collection DOAJ
description The fundamental stages in designing a stock portfolio are each stock’s selection and capital weighting. Selection and weighting must be conducted through diversification and price movement analysis to maximize profits and minimize losses. The problem is how the technical implementations of both are carried out. Based on this problem, this study aims to design these selection and weighting mechanisms. Stock selection is based on clusters and price movement trends. The optimal stock clusters are formed using the K-Means algorithm, and price movement analyses are carried out using the moving average indicator. The selected stocks are those whose prices have increasing trends with the most significant Sharpe ratio in each cluster. Then, the capital weighting for each preferred stock is carried out using the mean-variance model with transaction cost and income tax. After designing the mechanism, it is applied to Indonesia’s 80 index stock data. In addition, a comparison is conducted between the estimated portfolio return and the actual one day ahead. Finally, the sensitivity of investors’ courage in taking risks to their profits and losses is also analyzed. This research is expected to assist investors in diversification and price movement analysis of the stocks in the portfolios they form.
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spelling doaj.art-8d007e938013420b8dbc035c77495d902023-11-19T14:44:03ZengMDPI AGMathematics2227-73902023-10-011119415110.3390/math11194151Selecting and Weighting Mechanisms in Stock Portfolio Design Based on Clustering Algorithm and Price Movement AnalysisTiti Purwandari0Riaman1Yuyun Hidayat2Sukono3Riza Andrian Ibrahim4Rizki Apriva Hidayana5Department of Statistics, Faculty of Mathematics and Natural Sciences, Universitas Padjadjaran, Sumedang 45363, IndonesiaDepartment of Mathematics, Faculty of Mathematics and Natural Sciences, Universitas Padjadjaran, Sumedang 45363, IndonesiaDepartment of Statistics, Faculty of Mathematics and Natural Sciences, Universitas Padjadjaran, Sumedang 45363, IndonesiaDepartment of Mathematics, Faculty of Mathematics and Natural Sciences, Universitas Padjadjaran, Sumedang 45363, IndonesiaDoctoral Program of Mathematics, Faculty of Mathematics and Natural Sciences, Universitas Padjadjaran, Sumedang 45363, IndonesiaMagister Program of Mathematics, Faculty of Mathematics and Natural Sciences, Universitas Padjadjaran, Sumedang 45363, IndonesiaThe fundamental stages in designing a stock portfolio are each stock’s selection and capital weighting. Selection and weighting must be conducted through diversification and price movement analysis to maximize profits and minimize losses. The problem is how the technical implementations of both are carried out. Based on this problem, this study aims to design these selection and weighting mechanisms. Stock selection is based on clusters and price movement trends. The optimal stock clusters are formed using the K-Means algorithm, and price movement analyses are carried out using the moving average indicator. The selected stocks are those whose prices have increasing trends with the most significant Sharpe ratio in each cluster. Then, the capital weighting for each preferred stock is carried out using the mean-variance model with transaction cost and income tax. After designing the mechanism, it is applied to Indonesia’s 80 index stock data. In addition, a comparison is conducted between the estimated portfolio return and the actual one day ahead. Finally, the sensitivity of investors’ courage in taking risks to their profits and losses is also analyzed. This research is expected to assist investors in diversification and price movement analysis of the stocks in the portfolios they form.https://www.mdpi.com/2227-7390/11/19/4151selectingweightingstockportfolioclusteringprice movement analysis
spellingShingle Titi Purwandari
Riaman
Yuyun Hidayat
Sukono
Riza Andrian Ibrahim
Rizki Apriva Hidayana
Selecting and Weighting Mechanisms in Stock Portfolio Design Based on Clustering Algorithm and Price Movement Analysis
Mathematics
selecting
weighting
stock
portfolio
clustering
price movement analysis
title Selecting and Weighting Mechanisms in Stock Portfolio Design Based on Clustering Algorithm and Price Movement Analysis
title_full Selecting and Weighting Mechanisms in Stock Portfolio Design Based on Clustering Algorithm and Price Movement Analysis
title_fullStr Selecting and Weighting Mechanisms in Stock Portfolio Design Based on Clustering Algorithm and Price Movement Analysis
title_full_unstemmed Selecting and Weighting Mechanisms in Stock Portfolio Design Based on Clustering Algorithm and Price Movement Analysis
title_short Selecting and Weighting Mechanisms in Stock Portfolio Design Based on Clustering Algorithm and Price Movement Analysis
title_sort selecting and weighting mechanisms in stock portfolio design based on clustering algorithm and price movement analysis
topic selecting
weighting
stock
portfolio
clustering
price movement analysis
url https://www.mdpi.com/2227-7390/11/19/4151
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AT yuyunhidayat selectingandweightingmechanismsinstockportfoliodesignbasedonclusteringalgorithmandpricemovementanalysis
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