Stock Portfolio Optimization Using Single Index Model (SIM) with Exponentially Weighted Moving Average (EWMA) Approach

Authors

  • Ainul Mutmainna Department of Mathematics, Universitas Islam Negeri Alauddin Makassar
  • Nurwahidah Nurwahidah Department of Mathematics, Universitas Islam Negeri Alauddin Makassar
  • Sri Dewi Anugrawati Department of Mathematics, Universitas Islam Negeri Alauddin Makassar

DOI:

https://doi.org/10.29303/emj.v7i2.247

Keywords:

Portfolio, Single Index Model (SIM), Exponentially Weighted Moving Average (EWMA), K-Means Clustering

Abstract

The optimal portfolio is a combination of various assets with the aim of reducing investment risk through diversification. This study aims to conduct stock selection using K-Means Clustering and the formation of an optimal stock portfolio from the application of Single Index Model the amount of investment risk in the portfolio using the Exponentially Weighted Moving Average approach, and the amount of portfolio performance. The analysis results show that there are 5 portfolios formed. The best portfolio that can be chosen by investors depends on the investor's risk tolerance. Investors with low risk tolerance can choose Portfolio 3 consisting of ICBP and MIKA stocks with an expected return of 0.01343 and a risk of 0.00714 and a VaR of IDR 2,633,286.63. Investors with moderate risk tolerance can choose Portfolio 1 which consists of ICBP, MIKA, ACES, INCO, ITMG, MAPI, TPIA, AKRA, and MDKA stocks with an expected return of 0.022047, risk of 0.01277 and VaR of IDR 3,083,287.87. Investors with high risk tolerance can choose Portfolio 2 which consists of MIKA, TPIA, and MDKA stocks with an expected return of 0.02504 and a risk of 0.01471 and a VaR of IDR 3,553,167.10.

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Published

2024-12-14

How to Cite

Mutmainna, A., Nurwahidah, N., & Anugrawati, S. D. (2024). Stock Portfolio Optimization Using Single Index Model (SIM) with Exponentially Weighted Moving Average (EWMA) Approach. EIGEN MATHEMATICS JOURNAL, 7(2), 130–138. https://doi.org/10.29303/emj.v7i2.247

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